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3 Semester - 2022 - Batch | Paper Code |
Paper |
Hours Per Week |
Credits |
Marks |
AEN321 | ADDITIONAL ENGLISH | 3 | 3 | 100 |
ECO301 | RESEARCH METHODOLOGY FOR ECONOMICS | 2 | 2 | 50 |
ECO331 | FUNDAMENTALS OF ECONOMIC GROWTH AND DEVELOPMENT | 5 | 5 | 100 |
ENG321 | ENGLISH-III | 3 | 2 | 100 |
FRN321 | FRENCH | 3 | 3 | 100 |
HIN321 | HINDI | 3 | 3 | 100 |
KAN321 | KANNADA | 3 | 03 | 50 |
MAT331 | REAL ANALYSIS | 4 | 4 | 100 |
MAT351 | PYTHON PROGRAMMING FOR MATHEMATICS | 2 | 2 | 50 |
SAN321 | SANSKRIT | 3 | 3 | 100 |
STA331 | STATISTICAL INFERENCE | 4 | 4 | 100 |
STA351 | STATISTICAL INFERENCE PRACTICAL | 2 | 2 | 50 |
STA371 | APPLIED EXCEL | 4 | 4 | 100 |
TAM321 | TAMIL | 3 | 3 | 100 |
4 Semester - 2022 - Batch | Paper Code |
Paper |
Hours Per Week |
Credits |
Marks |
AEN421 | ADDITIONAL ENGLISH | 3 | 3 | 100 |
ECO401 | ADVANCED MICRO AND MACROECONOMICS | 2 | 2 | 50 |
ECO431 | INTERNATIONAL ECONOMICS | 5 | 5 | 100 |
ENG421 | ENGLISH-IV | 3 | 2 | 100 |
FRN421 | FRENCH | 3 | 3 | 100 |
HIN421 | HINDI | 3 | 3 | 100 |
KAN421 | KANNADA | 3 | 03 | 50 |
MAT431 | ALGEBRA | 4 | 4 | 100 |
MAT451 | PYTHON PROGRAMMING FOR MATHEMATICAL MODELLING | 2 | 2 | 50 |
SAN421 | SANSKRIT | 3 | 3 | 100 |
STA431 | ELEMENTS OF STOCHASTIC PROCESS | 4 | 4 | 100 |
STA451 | ELEMENTS OF STOCHASTIC PROCESS PRACTICAL | 2 | 2 | 50 |
TAM421 | TAMIL | 3 | 3 | 100 |
5 Semester - 2021 - Batch | Paper Code |
Paper |
Hours Per Week |
Credits |
Marks |
ECO532 | MATHEMATICAL ECONOMICS | 4 | 4 | 100 |
ECO541A | PUBLIC FINANCE | 4 | 4 | 100 |
ECO541C | ECONOMICS OF BANKING AND INSURANCE | 4 | 4 | 100 |
MAT511 | ANALYTICAL AND LOGICAL REASONING | 3 | 2 | 100 |
MAT531 | LINEAR ALGEBRA | 3 | 3 | 100 |
MAT541A | INTEGRAL TRANSFORMS | 3 | 3 | 100 |
MAT541B | MATHEMATICAL MODELLING | 3 | 3 | 100 |
MAT541C | GRAPH THEORY | 3 | 3 | 100 |
MAT541D | CALCULUS OF SEVERAL VARIABLES | 3 | 3 | 100 |
MAT541E | OPERATIONS RESEARCH | 3 | 3 | 100 |
MAT551 | LINEAR ALGEBRA USING PYTHON | 2 | 2 | 50 |
MAT551A | INTEGRAL TRANSFORMS USING PYTHON | 2 | 2 | 50 |
MAT551B | MATHEMATICAL MODELLING USING PYTHON | 2 | 2 | 50 |
MAT551C | GRAPH THEORY USING PYTHON | 2 | 2 | 50 |
MAT551D | CALCULUS OF SEVERAL VARIABLES USING PYTHON | 2 | 2 | 50 |
MAT551E | OPERATIONS RESEARCH USING PYTHON | 2 | 2 | 50 |
MAT581 | INTERNSHIP | 0 | 2 | 100 |
STA531 | LINEAR REGRESSION MODELS | 3 | 3 | 100 |
STA541A | SAMPLING TECHNIQUES | 3 | 3 | 100 |
STA541B | DESIGN OF EXPERIMENTS | 3 | 3 | 100 |
STA541C | ACTUARIAL STATISTICS | 3 | 3 | 100 |
STA541D | INTRODUCTION TO SPATIAL STATISTICS | 3 | 3 | 100 |
STA551 | LINEAR REGRESSION MODELS PRACTICAL | 2 | 2 | 50 |
STA552A | SAMPLING TECHNIQUES PRACTICAL | 2 | 2 | 50 |
STA552B | DESIGN OF EXPERIMENTS PRACTICAL | 2 | 2 | 50 |
STA552C | ACTUARIAL STATISTICS PRACTICAL | 2 | 2 | 50 |
STA552D | SPATIAL STATISTICS PRACTICAL | 2 | 2 | 50 |
6 Semester - 2021 - Batch | Paper Code |
Paper |
Hours Per Week |
Credits |
Marks |
ECO631 | INTRODUCTION TO ECONOMETRICS | 4 | 4 | 100 |
ECO641A | ENVIRONMENTAL ECONOMICS | 4 | 4 | 100 |
ECO641B | FINANCIAL ECONOMICS | 4 | 4 | 100 |
MAT631 | COMPLEX ANALYSIS | 3 | 3 | 100 |
MAT641A | MECHANICS | 3 | 3 | 100 |
MAT641B | NUMERICAL METHODS | 3 | 3 | 100 |
MAT641C | DISCRETE MATHEMATICS | 3 | 3 | 100 |
MAT641D | NUMBER THEORY | 3 | 3 | 100 |
MAT641E | FINANCIAL MATHEMATICS | 3 | 3 | 100 |
MAT651 | COMPLEX ANALYSIS USING PYTHON | 2 | 2 | 50 |
MAT651A | MECHANICS USING PYTHON | 2 | 2 | 50 |
MAT651B | NUMERICAL METHODS USING PYTHON | 2 | 2 | 50 |
MAT651C | DISCRETE MATHEMATICS USING PYTHON | 2 | 2 | 50 |
MAT651D | NUMBER THEORY USING PYTHON | 2 | 2 | 50 |
MAT651E | FINANCIAL MATHEMATICS USING EXCEL AND PYTHON | 2 | 2 | 50 |
MAT681 | PROJECT ON MATHEMATICAL MODELS | 5 | 5 | 150 |
STA631 | TIME SERIES ANALYSIS AND FORECASTING TECHNIQUES | 3 | 3 | 100 |
STA641A | APPLIED STATISTICS | 3 | 3 | 100 |
STA641B | STATISTICAL QUALITY CONTROL | 3 | 3 | 100 |
STA641C | BIOSTATISTICS | 3 | 3 | 100 |
STA641D | STATISTICAL GENETICS | 3 | 3 | 100 |
STA651 | TIME SERIES ANALYSIS AND FORECASTING TECHNIQUES PRACTICAL | 2 | 2 | 50 |
STA652A | APPLIED STATISTICS PRACTICAL | 2 | 2 | 50 |
STA652B | STATISTICAL QUALITY CONTROL PRACTICAL | 2 | 2 | 50 |
STA652C | BIOSTATISTICS PRACTICAL | 2 | 2 | 50 |
STA652D | STATISTICAL GENETICS PRACTICAL | 2 | 2 | 50 |
AEN321 - ADDITIONAL ENGLISH (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description
This course is taught in the second year for students from different streams, namely BA, BSc
and BCom. If the first year syllabus is an attempt by the Department of English, Christ
University to recognize and bring together the polyphonic Indian voices in English and Indian
regional literatures in translation for the Additional English students of the first year, the
second year syllabus intends to take that project a little further and open up the engagement
of the students to texts from across the world. The syllabus - selection of texts will
concentrate on readings from South Asian, Latin American, Australian, Canadian, and Afro-
American. It will voice subaltern concerns of identity, gender, race, ethnicity and problems of
belongingness experienced by humanity all over the globe.
The syllabus will extend the concerns of nation and nationality and marginalization,
discussed within the Indian context to a more inclusive and wider global platform. We have
consciously kept out ‘mainstream’ writers and concentrated on the voices of the subalterns
from across the world. There is an implicit recognition in this project that though the aspects
of marginalization and the problems facing subalterns are present across cultures and
nations, the experiences, expressions and reflections are specific to each race and culture.
The course will address these nuances and specificities and enable our students to become
more aware and sensitive to life and reality around them. This will equip the students, who
are global citizens, to understand not just the Indian scenario, but also situate themselves
within the wider global contexts and understand the spaces they will move into and negotiate
in their future.
There is a prescribed text book Blends: Voices from Margins for the second year students,
compiled by the Department of English, Christ University and intended for private circulation. Course Objectives
The course objectives are
to enable students to look at different cultures through Literature
to help students develop an understanding of subaltern realities and identity politics
to inculcate literary sensibility/taste among students across disciplines
to improve language skills –speaking, reading, writing and listening
to equip the students with tools for developing lateral thinking
to equip students with critical reading and thinking habits
to reiterate the study skills and communication skills they developed in the previous
year and extend it. |
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Learning Outcome |
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CO1: it will enable students to understand and analyse the nuances of cultures, ethnicities and other diversity around them and become sensitive towards them. CO2 : They will be able to critique literature from a cultural, ethical, social and political perspectives
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
ECO301 - RESEARCH METHODOLOGY FOR ECONOMICS (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course is designed to enable students to understand the importance of research in creating and extending the knowledge base in their research interests. In this process, it develops the students' ability to distinguish between the strengths and limitations of different research approaches in general and in their research area specifically. Finally, the course imparts skills to work independently, to plan and carry out a small-scale research project. |
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Learning Outcome |
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CO1: Demonstrate knowledge of research processes (reading, evaluating, and developing). CO2: Perform literature reviews using print and online databases. CO3: Employ American Psychological Association (APA) formats for citations of print and electronic materials. CO4: Identify, explain, compare, and prepare the key elements of a research proposal/report. CO5: Define and develop a possible research interest area using specific research designs. CO6: Acquire skills to work independently to plan and carry out a small-scale research project. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
ECO331 - FUNDAMENTALS OF ECONOMIC GROWTH AND DEVELOPMENT (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:5 |
Course Objectives/Course Description |
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The course is intended to give an understanding of the theoretical perceptions of economic growth and development together with the forces bringing about them. It also helps to broaden the awareness of the challenges in the developmental process and thus motivate the students towards the thought process of alternative solutions. |
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Learning Outcome |
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The students will 1. Gain conceptual base in Economic Dvelopment and Growth. 2. Familiarise with key models and theories in Dvelopment and Growth. 3. Gain insight in to the key issues of economic development. 4. Get awareness of the approaches to development efforts. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
ENG321 - ENGLISH-III (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Course Description English is offered as a course for all the students in BA, BSc, BCom, and BBA F&A classes in the third and fourth semesters. The aim is to strengthen the communication skills, and particularly study skills of the learners further, through adequate practice and exposure to good examples of writing, thought, ideas and human values. In addition, they will be trained in study skills through tasks in academic genres such as message, letter, essay, data interpretation etc. It aims to not only equip learners with skills but also sensitize them towards issues that concern human life in today’s globalised context. The course content is selected to meet the requirements of the departmental goal of “empowering the individual to read oneself, the social context and the imagined”; institutional goal of ensuring “holistic development”; and the national goal of creating competent and valuable citizens. The primary objective of this course is to help learners develop appropriate employability skills and demonstrate suitable conduct with regards to communication skills. The units are organised in order to help the learners understand the academic and workplace demands and learn by practice.
Course Objectives
· To enable learners to develop reading comprehension for various purposes
· To enable learners to develop writing skills for academic and professional needs
· To enable learners to develop the ability to think critically and express logically
· To enable learner to communicate in a socially and ethically acceptable manner
· To enable learners, to read, write and speak with clarity, precision and accuracy
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Learning Outcome |
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CO1: Recognise the errors of usage and correct them. Recognize their own ability to improve their own competence in using the language CO2: Read independently unfamiliar texts with comprehension. Read longer texts, compare, and evaluate them. CO3: Understand the importance of writing in academic life. Write simple sentences without committing errors in spelling and grammar. Plan a piece of writing using drafting techniques. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
FRN321 - FRENCH (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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French as second language for the Arts, Science and Commerce UG program |
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Learning Outcome |
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CO1: Ability to communicate with native speakers and make presentations on small topics
CO 2: Proficiency in literary analysis, appreciation and review of poems,play ,films and fables CO3: Acquaintance of culture, civilization, social values and etiquettes, and gastronomical richness
CO 4: Ability to do formal and informal, oral and written communication. CO 5: Overall knowledge on functional and communicative aspects and get through a2 level exams.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
HIN321 - HINDI (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
Course Description: The detailed text book “Shambook” is a Khanda Kavya written by Jagdeesh Gupta. To improve the creative writing skills, Nibandh, Kahani and Kavitha lekhan are included.Bharathiya chitrakala is also a part of the syllabus to improve the knowledge aboutIndian paintings. Course Objectives: Students are exposed to different forms of poetry especially, Khanda Kavya. It will help them to understand the contemporary socio-political issues.By learning about the tradition of Indian painting and legendary painters of India , students get to know about the richness and culture of the Indian paintings. Creative writing sharpens their thinking, analytical and writing skills |
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Learning Outcome |
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CO1: By the end of the course the student should be able to:
● CO1: Improve their writing skill in literary Hindi by doing asynchronous session assignments and CIAs.
● CO2: Improve their analytical skills through critical analysis of the poetry.
● CO3: Will be able to learn the different aspects of Official correspondence.
● CO4: To improve their basic research skills while doing the CIAs.
By the end of the course the student should be able to:
● CO1: Improve their writing skill in literary Hindi by doing assignments and CIAs
CO2: Improve their analytical skills through critical analysis of the poetry. CO3: To improve their basic research skills while doing the CIAs CO4: To understand the contributions of painters to Indian painting. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
KAN321 - KANNADA (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:03 |
Course Objectives/Course Description |
|
Course Description: Language Kannada is offered to students of third Semester BA/B.Sc as Second language for fifty marks. Students of this semester will study an anthology of Modern Kannada Poetry and an Autobiography of Laxman Gaikwad. This course prepares the students to understand the new era. At the dawn of the twentieth century, B.M. Srikantiah, regarded as the “Father of modern Kannada Literature”, called for a new era of writing original works in modern Kannada while moving away from archaic Kannada forms. Students will study modern Kannada poetry from B.M.Sri to Dalit poet Dr. Siddalingiah. An anthology of modern poetry is selected to understand the beauty of modern Kannada poets through their writings. Uchalya is an autobiographical novel that carries the memories of Laxman Gaikwad right from his childhood till he became an adult. Laxman Gaikwad took birth in a criminal tribe of India belonging to Orissa/ Maharastra. The original text is translated to Kannada by Chandrakantha Pokale.
Course Objectives: Understand and appreciate poetry as a literary art form. Analyse the various elements of Poetry, such as diction, tone, form, genre, imagery, symbolism, theme, etc. Appreciates to learn the elements of autobiography. |
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Learning Outcome |
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CO 1: Able to define autobiography CO2: Outline a personal autobiography CO3: Delineate different types of autobiography CO 4: Proficiency in communication skills CO5 : Understand the principles of translation |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MAT331 - REAL ANALYSIS (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
Course description : This course enables the students to understand the basic techniques and theories of real Analysis.
Course objectives : This course will help the learner to COBJ1. examine the convergence or divergence of sequences and series. COBJ2. understand the different types of convergence and their properties.
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Learning Outcome |
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Course outcomes : On successful completion of the course, the students should be able to CO1. Quote and understand the definition of a limit of a sequence or a function in its various forms. CO2. Demonstrate the convergence or divergence of the geometric and harmonic series and other standard series. CO3. Apply the basic tests for convergence of infinite series. CO4. Prove the tests for convergence: Comparison Test, Ratio Test, Cauchy’s Root test, Raabe’s Test, alternating series test etc. CO5. Understand the differences between convergence and absolute convergence CO6. Understand and solve binomial , logarithmic and exponential series |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MAT351 - PYTHON PROGRAMMING FOR MATHEMATICS (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
|
Course description: The course Python programming for Mathematics is aimed at enabling the students to appreciate and understand some concepts in mathematics like Matrices, sequences, series, geometric shapes and fractals with the help of Python programming language. It is designed with a learner-centric approach wherein the students will acquire mastery in the subject by using Python programing language as tool. Course objectives: This course will help the learner to COBJ1. Acquire programming skill in solving mathematical problems using Python |
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Learning Outcome |
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CO1: demonstrate the use of Python to understand and interpret the concepts in sequences and series. CO2: apply Python to finding the area of the curve. CO3: acquire proficiency in using Python to find out the inverse determinant, transpose, Eigen values of a Matrix. CO4: visualize shapes and Fractals |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
SAN321 - SANSKRIT (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Sundara Kanda is the only chapter of the Ramayana in which the hero is not Rama, but rather Hanuman. The work depicts the adventures of Hanuman and his selflessness, strength, and devotion to Rama are emphasized in the text. Bhoja only wrote 5 kāṇdas (up to the Sundarakāṇda), and there is a story about this: that he was inspired to write this work the night before a battle, that as he finished the Sundarakāṇda it was time to go, and that he announced that the Yuddhakāṇda would be enacted in the battlefield against the invader, but sadly he never returned. Others have composed a Yuddhakāṇda to complete the work. The main objective of the students is to understand the champu Kavyas based on the sam. The Origin and development of the Champu. |
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Learning Outcome |
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CO1: To analyse the content of the text in detail with examples CO2: To Deliberate the classification and characters of the epic CO3: To understand the delight of the text. CO4: To demonstrate an increased ability to read and understand Sanskrit texts CO5: To understand the prefixes and suffixes and changing the sentences in grammar. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
STA331 - STATISTICAL INFERENCE (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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This course is designed to introduce the concepts of theory of estimation and testing of hypothesis. This paper also deals with the concept of parametric tests for large and small samples. It also provides knowledge about non-parametric tests and its applications. |
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Learning Outcome |
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CO1: Demonstrate the concepts of point and interval estimation of unknown parameters and their significance using large and small samples. CO2: Apply the idea of sampling distributions of difference statistics in testing of hypotheses.
CO3: Apply the concept of nonparametric tests for single sample and two samples. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
STA351 - STATISTICAL INFERENCE PRACTICAL (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course is designed to give a practical exposure for testing of hypothesis by analyzing various data sets using R programming. |
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Learning Outcome |
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CO1: Demonstrate the parametric tests for small and large samples using R programming. CO2: Demonstrate the non-parametric tests for real time data using R programming. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
STA371 - APPLIED EXCEL (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
Course description: This course is designed to build the logical thinking ability and to provide hands-on experience in solving statistical models using MS Excel with Problem based learning. To explore and visualize data using excel formulas and data analysis tool pack.
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Learning Outcome |
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CO1: Demonstrate the logics of using excel features.
CO2: Demonstrate the building blocks of excel, excel shortcuts, sample data creation and analyzing data.
CO3: Analyze the data sets using Data Analysis Pack. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
TAM321 - TAMIL (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
Araillakiyam, bakthi illakiyam, ikala illakiyamn the major allakiyams.The influence myths and puranas are delineated through the good deeds for a better lifestyle.The Cultural Studies part will have an overview of Indian painting both traditional and modern with special reference to mythology and literature India 2020- Abdul Kalam
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Learning Outcome |
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CO1: Recall and categorize the concepts of literature. CO2: Understand the true essence of the texts, and inculcate them in their daily lives. CO3: Recognize and apply the moral values and ethics in their learning. CO4: Comprehend the concepts in literature and appreciate the literary text. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
AEN421 - ADDITIONAL ENGLISH (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
This course is taught in the second year for students from different streams, namely BA, BSc and B Com. If the first year syllabus is an attempt by the Department of English, Christ University to recognize and bring together the polyphonic Indian voices in English and Indian regional literatures in translation for the Additional English students of the first year, the second year syllabus intends to take that project a little further and open up the engagement of the students to texts from across the world. The syllabus - selection of texts will concentrate on readings from South Asian, Latin American, Australian, Canadian, and Afro-American. It will voice subaltern concerns of identity, gender, race, ethnicity and problems of belongingness experienced by humanity all over the globe. The syllabus will extend the concerns of nation and nationality and marginalization, discussed within the Indian context to a more inclusive and wider global platform. We have consciously kept out ‘mainstream’ writers and concentrated on the voices of the subalterns from across the world. There is an implicit recognition in this project that though the aspects of marginalization and the problems facing subalterns are present across cultures and nations, the experiences, expressions and reflections are specific to each race and culture. The course will address these nuances and specificities and enable our students to become more aware and sensitive to life and reality around them. This will equip the students, who are global citizens, to understand not just the Indian scenario, but also situate themselves within the wider global contexts and understand the spaces they will move into and negotiate in their future.
There is a prescribed text book Blends: Voices from Margins for the second year students, compiled by the Department of English, Christ University and intended for private circulation. The course objectives are · to introduce the students to look at different cultures through Literature · to help students develop an understanding of subaltern realities and identity politics · to inculcate literary sensibility/taste among students across disciplines · to improve language skills –speaking, reading, writing and listening · to equip the students with tools for developing lateral thinking · to equip students with critical reading and thinking habits · to enable them to grasp and appreciate the variety and abundance of subaltern writing, of which this compilation is just a glimpse · to actively engage with the world as a cultural and social space (to be facilitated through proactive CIAs which help students to interact and engage with the realities they face everyday and have come across in these texts) · to learn and appreciate India and its place in the world through association of ideas in the texts and the external contexts
· to reiterate the study skills and communication skills they developed in the previous year and extend it. |
|
Learning Outcome |
|
CO1 : CO1: To understand the socio- political concerns in various literatures through short stories, poems and essays
CO2: CO2: To critically read and articulate the non- canonised literatures
CO3: CO3: To analyse and apply these textual themes in a multi- cultural, global and professional space
|
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
ECO401 - ADVANCED MICRO AND MACROECONOMICS (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
|
The course is designed to provide a sound understanding of some of the advanced concepts in Microeconomics and Macroeconomics. The course combines mathematical approach along with the geometric approach to economic theory and includes some intermediate concepts, which aim to bridge the gap between the Principles of Microeconomics and Macroeconomics that the students have studied in the first year and the Mathematical Economics. |
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Learning Outcome |
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· Sound understanding of the concepts at the intermediate level relating to consumer behavior, production and market structure · Students will get familiar with the mathematical approach to economic analysis Understanding of the macroeconomic functioning of the economy |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
ECO431 - INTERNATIONAL ECONOMICS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:5 |
Course Objectives/Course Description |
|
The aim of this paper is to provide students with strong foundation in the principles of international economics which will help them to know the trade policies at the national and international levels and the impact of the globalization on income, employment and social standards in the current international scenario. The paper also covers the pure theory of trade and extensions thereof, customs union, and balance of payments adjustment policies under alternative exchange-rate regimes including the determination of the exchange rate. |
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Learning Outcome |
|
CO1: gain a strong foundation in the principles of international economics. CO2: be able to know the trade policies at the national and international levels and the impact of globalization on income, employment and social standards in the current international scenario. CO3: gain an understanding of the trade policies. |
Unit-1 |
Teaching Hours:6 |
Introduction and Essentials
|
|
The Subject Matter of International Economics; Trade Based on Absolute Advantage; Trade Based on Comparative Advantage; Comparative Advantage and Opportunity Costs; Empirical Tests of the Ricardian Model. | |
Text Books And Reference Books: Dominick Salvatore (2011), International Economics: Trade and Finance, John Wiley International Student Edition, 10th Edition. | |
Essential Reading / Recommended Reading Dominick Salvatore (2011), International Economics: Trade and Finance, John Wiley International Student Edition, 10th Edition. | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
ENG421 - ENGLISH-IV (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
|
This syllabus is meant to cater to all the three streams- B.A., B.Sc.and B.Com therefore the selection of units, has been done keeping in mind the general needs of students from these different backgrounds. Topics of universal concern, appeal and relevance have been included to sustain the interests of all students.
The selection of topics also progresses in complexity with each semester, enabling the students to gradually progress into more serious and sustained patterns of reading and become increasingly perceptive and conscious of their own selves and the world they see around them.In a nutshell we aim to bring out a text that will empower the holistic development of every student.
In addition, the selection of topicsis also heavily based on skill sets identified to be taught. Topics are carefully chosen to integrate appropriate language and communication skills among students. The specific focus of these two semesters is to build employability skills among them and to this effect, we have career advancement skills and employability skills based units. The learners will be exposed to various skill sets required to be able to handle various requirements both in their academic and workplaces.
Course Objectives:
· To enable learners to develop reading comprehension for various purposes
· To enable learners to develop writing skills for academic and professional needs
· To enable learners to develop the ability to think critically and express logically
· To enable learner to communicate in a socially and ethically acceptable manner
· To enable learners, to read, write and speak with clarity, precision and accuracy
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Learning Outcome |
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CO1: Ability to judge audience requirements in oral and written communication and communicate accordingly. CO2: Ability to use specific styles in communication and understand workplace structures and requirements to communicate CO3: Lead and participate in seminars and group discussions more effectively and with increased confidence. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
FRN421 - FRENCH (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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French as a second language in the UG program. The method Génération A2 consists of a student's book and an activity book, both included in the digital manual. It consists of 6 units preceded by an initial section of 'Welcome'. Continuing from where A1 left, it aims to enhance learning skills further. The structure of each unit marks a real learning journey into different aspects of the French language and culture.
Course Objectives · To develop linguistic competencies and sharpen oral and written communicative skills further · To enhance awareness of different aspects of francophone civilization. · To enrich the learner’s vocabulary · To enable learners to engage in and discuss simple topics with ease
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Learning Outcome |
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CO1: To familiarize students with the French culture and traditions. CO 2: To equip students with correct grammar, vocabulary and pronunciation. CO3: To enhance communicative skills. CO 4: To make them well versed in all the four language skills. CO5: To make them ready for A2 level Exams. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
HIN421 - HINDI (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: The detailed text-book "Ashad ka ek din” is a drama by Mohan Rakeshi, one of the eminent writers of modern Hindi Literature. Hindi journalismis is one of the major unit of this semester. Phrases, idioms, technical and scientific terminology are included in this semester to improve the literary skills. Course Objectives: Through the prescribed play and the theatre performance, students can go through the process of experiential learning. Study of Mass media enables them to get practical training. Phrases, idioms, technical and scientific terminology sharpen the language skills of the students.
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Learning Outcome |
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CO1 : Understand the nuances of Hindi theatre. CO2: Create awareness of the social issues. CO3: Improve the skill of critical analysis. CO4: Develop the writing skills for media. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
KAN421 - KANNADA (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:03 |
Course Objectives/Course Description |
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The course introduces the rich Kannada language and helps students to read and write the Regional language effectively. The prescribed text ‘Kalagnani Kanaka’ (Kanaka, the visionary) is all about 15th century poet, saint and philosopher of the Haridasa Bhakti tradition. “Kanaka’s writings touch on all aspects of truth and social reality’ said K.R. Nagaraj, literary critic and the author of the Kalagnani Kanaka play. “Kanaka’s poetry is dense with rhyme, rhythm, meter and rich descriptions. He upholds social justice while addressing the issues of the time-caste and class differentiation and gender oppression, for example. Contrary to popular belief, he never confined himself to any one philosophical tradition- Advaita, Dwaita or Vishistadwaitha” ‘Kannadada Moovattu Kathegalu’ is another prescribed text. Through this text the students are exposed to the writings of Koradkal Sreenivasa Rao, K. P. Poornachandra Tejaswi, Masti Venkatesha Iyengar, G. P. Basavaraj and others. Short stories help students in harnessing creative writing skills. |
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Learning Outcome |
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CO1: Reflects the tradition of old & the new CO2: Helps to create dialogue writing CO3: Identify key points in stories CO4: Understand the ideologies during British rule CO5: Expose to Dasa Sahitya movement |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT431 - ALGEBRA (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course description : This course aims at developing the ability to write the mathematical proofs. It helps the students to understand and appreciate the beauty of the abstract nature of mathematics and also to develop a solid foundation of theoretical mathematics. Course objectives : This course will help the learner to COBJ1. Understand the fundamentals of groups and its theories. COBJ2. Relate abstract algebraic constructs to more familiar sets and operators COBJ3. Know about the subgroups and group homomorphisms COBJ4. Get familiar with the theories on rings, integral domains and fields. |
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Learning Outcome |
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CO1: Describe and generate groups, rings and fields. CO2: Identify and differentiate different structures and understand how changing properties give rise to new structures. CO3: Demonstrate the knowledge of concepts of rings and fields. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT451 - PYTHON PROGRAMMING FOR MATHEMATICAL MODELLING (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: The course Python programming for mathematical modelling is aimed at enabling the students study the implementation of Python programming for solving some real world problems. It is designed with a learner-centric approach wherein the students will acquire mastery in the modelling and simulation by using Python programming language as a tool. Course objectives: This course will help the learner to COBJ1. Acquire proficiency in using Python to present data grapically COBJ2. Solving differential equations analytically and numerically using Python. COBJ3. Acquire skills to solve various Mathematical models- exponential growth, Logistic growth, simple pendulum and spreading of disease. |
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Learning Outcome |
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CO1: Solve differential equations governed by mathematical models using Python. CO2: Demonstrate the use of Python to interpret and analyze the data. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
SAN421 - SANSKRIT (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Avimarakam by Bhasa is the drama prescribed as a text and approved in the B.O.S. It is sociological drama which explains about the society. . This drama is an imaginary composition of Bhasa . The concept and drama skills expresses the beauty of the style of the author Bhasa. He creates the characters and the incidents are naturally created. Grammar will also be studied. |
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Learning Outcome |
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CO1: To Understand the style and development of the play CO2: To learn the linguistic skills of the drama. CO3: To Deliberate the classification and characteristics of the play CO4: To Understand the features of play CO5: To understand the basic structural nuances of Panini?s grammar |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA431 - ELEMENTS OF STOCHASTIC PROCESS (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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This course designed to introduce the concepts, models and problem solving techniques of stochastic process. |
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Learning Outcome |
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CO1: Solve the problems related to business or industry which are stochastic in nature. CO2: Demonstrate the different queuing systems and methods to solve the queuing problems. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA451 - ELEMENTS OF STOCHASTIC PROCESS PRACTICAL (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course is designed to teach practical Stochastic process problems using statistical softwares. |
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Learning Outcome |
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CO1: Demonstrate and evaluate stochastic models using statistical softwares. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
TAM421 - TAMIL (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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A new concept, cultural studies, will take the students beyond prescribed syllabus to include music, theatre, painting, and films out of which the art form of music is taken up for the first semester. Aram poetry- Ara nericharam specifies life discipline and standards, which would pave a successful life for the students. Bhakthi ilakiya- them bhavani, cheerapuranam, thirumandiram is inclined towards ritual practices. Kaapiyam with its historical values provides an understanding about life in a mature way. |
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Learning Outcome |
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CO1: Recall and categorize the concepts of literature.
CO2: Understand the true essence of the texts, and inculcate them in their daily lives. CO3: Recognize and apply the moral values and ethics in their learning. CO4: Comprehend the concepts in literature and appreciate the literary text. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
ECO532 - MATHEMATICAL ECONOMICS (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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The main objectives of the paper are to train the students to grasp the use of mathematical techniques and operations to analyse economic problems and to initiate students into various economic concepts which are amenable to mathematical treatment. |
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Learning Outcome |
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CO1: Possess a solid grasp of essential mathematical tools required for the further studies in economic theory. CO2: Use and explain the underlying principles, terminology, methods, techniques and conventions used in the subject CO3: Develop an understanding of optimization techniques used in economic theory. CO4: Solve economic problems using the mathematical methods described in the course. |
Text Books And Reference Books: | ||
Essential Reading / Recommended Reading | ||
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | ||
ECO541A - PUBLIC FINANCE (2021 Batch) | ||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Learning Outcome |
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CO1: List out various reasons for the market failure and mechanisms to deal with market failure situation. CO2: Demonstrate a good understanding of the fiscal framework for taxing and spending and of fiscal policy principles CO3: Examine key issues and challenges in fiscal policy in a particular development or country context. CO4: Discuss the reasons for government intervention in the economy as well as different types of regulation CO5: Evaluate and compare different policies of taxation, public expenditure and public borrowing and public borrowing |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
ECO541C - ECONOMICS OF BANKING AND INSURANCE (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description This is an elective course. This course attempts to make students understand the broad functioning of a bank both at the macro and micro levels and measure the performance of banks. The said course also offers basic knowledge about the uniqueness of the Insurance business and thereby enables the participants to understand the multi-disciplinary functions of an Insurance organization. Course Objectives This course enables the participants to understand the multi-disciplinary functions of a banking sector and also Insurance organization both at the macro and micro levels. |
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Learning Outcome |
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CO1: Understanding the various practices related to banking and insurance and prepares students for a career in this field. CO2: Examine various aspects of risk management through life and non-life insurance products including their structure. CO3: Demonstrate the application of the concepts and principles of banking and insurance in real-world situations |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT511 - ANALYTICAL AND LOGICAL REASONING (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Analytical and Logical Training Skills is an add-on course. This course is designed in a way that inculcates the habit of application of concepts thereby paving way for effective learning and optimal utilization of time. It is specially designed for high performance in Quantitative, reasoning and general knowledge sections of various examinations.
Course Objective: This course will the learner to COBJ1, enhance aptitude and reasoning skills COBJ2. quickly answer the questions on quantitative, reasoning and general knowledge COBJ3. face competitive examinations boldly and be successful also. |
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Learning Outcome |
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CO1: Solve questions based on Logic, Reasoning, Basic Numeracy and Arithmetic aptitude. CO2: Recognize the pattern and approach to questions based on Verbal and Quantitative reasoning. CO3: Improve Speed and Accuracy in solving Multiple Choice based questions.
CO4: Improve General awareness and knowledge base of the students. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT531 - LINEAR ALGEBRA (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course aims at developing the ability to write the mathematical proofs. It helps the students to understand and appreciate the beauty of the abstract nature of mathematics and also to develop a solid foundation of theoretical mathematics. Course Objectives : This course will help the learner to COBJ1. understand the theory of matrices, concepts in vector spaces and Linear Transformations. COBJ2. gain problems solving skills in solving systems of equations using matrices, finding eigenvalues and eigenvectors, vector spaces and linear transformations. |
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Learning Outcome |
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CO1: use properties of matrices to solve systems of equations and explore eigenvectors and eigenvalues. CO2: understand the concepts of vector space, basis, dimension, and their properties. CO3: analyse the linear transformations in terms of matrices. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT541A - INTEGRAL TRANSFORMS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course aims at providing a solid foundation upon the fundamental theories on Fourier and Laplace transforms. |
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Learning Outcome |
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CO1: Evaluate integrals by using Fourier series and Fourier integrals. CO2: Apply Fourier sine and cosine transforms for various functions. CO3: Derive Laplace transforms of different types of functions. CO4: Utilize the properties of Laplace transforms in solving ordinary differential equations. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT541B - MATHEMATICAL MODELLING (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course is concerned with the fundamentals of mathematical modeling. It deals with finding solution to real world problems by transforming into mathematical models using differential equations. The coverage includes mathematical modeling through first order, second order and system of ordinary differential equations.
This course will help the learner to COBJ1. interpret the real-world problems in the form of first and second order differential equations. COBJ2. familiarize with some classical linear and nonlinear models. COBJ3. analyse the solutions of systems of differential equations by phase portrait method. |
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Learning Outcome |
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CO1: Apply differential equations in other branches of sciences, commerce, medicine and others CO2: Understand the formulation of some classical mathematical models. CO3: Demonstrate competence with a wide variety of mathematical tools and techniques. CO4: Build mathematical models of real-world problems. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT541C - GRAPH THEORY (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description:This course is an introductory course to the basic concepts of Graph Theory. This includes definition of graphs, types of graphs, paths and circuits, trees, shortest paths and algorithms to find shortest paths. Course objectives: This course will help the learner to COBJ 1: Gain conceptual knowledge on terminologies used in graph theory.
COBJ 2: Understand the results on graphs and their properties. COBJ 3: Gain proof writing and algorithm writing skills. |
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Learning Outcome |
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CO1: understand the terminology related to graphs CO2: analyze the characteristics of graphs by using standard results on graphs CO3: apply proof techniques and write algorithms |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT541D - CALCULUS OF SEVERAL VARIABLES (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: This course aims to enlighten students with the fundamental concepts of vectors, geometry of space, partial differentiation and vector analysis such as gradient, divergence, curl, and the evaluation of line, surface and volume integrals. The three classical theorems, viz., Green’s theorem, Gauss divergence theorem and the Stoke’s theorem are also covered. Course objectives: This course will help the learner to COBJ1. Gain familiarity with the fundamental concepts of vectors geometry of space. COBJ2. Understand differential and integral calculus of vector fields. COBJ3. Demonstrate an understanding of and be able to use Green’s Theorem for the plane, Stokes Theorem, and Gauss’ divergence Theorem to simplify and solve appropriate integrals. |
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Learning Outcome |
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CO1: Solve problems involving vector operations. CO2: Understand the TNB frame work and derive Serret-Frenet formula. CO3: Compute double integrals and be familiar with change of order of integration.
CO4: Understand the concept of line integrals for vector valued functions. CO5: Apply Green's Theorem, Divergence Theorem and Stoke's Theorem. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT541E - OPERATIONS RESEARCH (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course description: Operations research deals with the problems on optimization or decision making that are affected by certain constraints / restrictions in the environment. This course aims at teaching solution techniques of solving linear programming models, simple queuing model, two-person zero sum games and Network models. Course objectives: This course will help the learner to COBJ1. gain an insight executing the algorithms for solving linear programming problems including transportation and assignment problems. COBJ2. learn about the techniques involved in solving the two person zero sum game. COBJ3. calculate the estimates that characteristics the queues and perform desired analysis on a network. |
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Learning Outcome |
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CO1: On successful completion of the course, the students should be able to solve Linear Programming Problems using Simplex Algorithm, Transportation and Assignment Problems.
CO2: On successful completion of the course, the students should be able to find the estimates that characterizes different types of Queuing Models.
CO3: On successful completion of the course, the students should be able to obtain the solution for two person zero sum games using Linear Programming. CO4: On successful completion of the course, the students should be able to formulate Maximal Flow Model using Linear Programming and perform computations using PERT and CPM. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT551 - LINEAR ALGEBRA USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: This course aims at providing hands on experience in using Python functions to illustrate the notions vector space, linear independence, linear dependence, linear transformation and rank. Course objectives: This course will help the learner to COBJ1. The built in functions required to deal with vectors and Linear Transformations. COBJ2. Python skills to handle vectors using the properties of vector spaces and linear transformations |
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Learning Outcome |
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CO1: Use Python functions in applying the notions of matrices and system of equations.
CO2: Use Python functions in applying the problems on vector space.
CO3: Apply python functions to solve the problems on linear transformations.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT551A - INTEGRAL TRANSFORMS USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course will help students to gain skills in using Python to illustrate Fourier transforms, Laplace transforms for some standard functions and implementing Laplace transforms in solving ordinary differential equations of first and second order with constant coefficient. Course Objectives: This course will help the learner to COBJ 1:code python language using jupyter interface. COBJ 2:use built in functions required to deal with Fourier and Laplace transforms. COBJ 3: calculate Inverse Laplace transforms and the inverse Fourier transforms of standard functions using sympy.integrals |
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Learning Outcome |
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CO1.: Acquire skill in Python Programming to illustrate Fourier series, Fourier and Laplace transforms. CO2.: Use Python program to solve ODE?s by Laplace transforms. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT551B - MATHEMATICAL MODELLING USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: This course provides students with an understanding of the practical and theoretical aspects of mathematical models involving ordinary differential equations (ODEs) using Python programming. Course objectives: COBJ1. The course exposes students to various models spanning disciplines such as physics, biology, engineering, and finance. COBJ2. They will be able to develop a basic understanding of differential equations and skills to implement numerical algorithms to solve mathematical problems using Python. |
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Learning Outcome |
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CO1: Acquire proficiency in using Python. CO2: Demonstrate the use of Python to understand and interpret applications of differential equations CO3: Apply the theoretical and practical knowledge to real life situations. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT551C - GRAPH THEORY USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: The course graph theory using Python is aimed at enabling the students to appreciate and understand core concepts of graph theory with the help of technological tools. It is designed with a learner-centric approach wherein the students will understand the concepts of graph theory using programming tools and develop computational skills. Course objectives: This course will help the learner to COBJ1. Gain familiarity in Python language using jupyter interface and NetworkX package COBJ2. Construct graphs and analyze their structural properties. COBJ3. Implement standard algorithms for shortest paths, minimal spanning trees and graph searching.. |
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Learning Outcome |
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CO1: construct graphs using related matrices CO2: compute the graph parameters related to degrees and distances CO3: gain mastery to deal with optimization problems related to networks CO4: apply algorithmic approach in solving graph theory problems |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT551D - CALCULUS OF SEVERAL VARIABLES USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: The course calculus of several variables using python is aimed at enabling the students to explore and study the calculus with several variables in a detailed manner with the help of the mathematical packages available in Python. This course is designed with a learner-centric approach wherein the students will acquire mastery in understanding multivariate calculus using Python modules. Course objectives: This course will help the learner to gain a familiarity with COBJ1. Skills to implement Python language in calculus of several variables COBJ2. The built-in functions available in library to deal with problems in multivariate calculus |
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Learning Outcome |
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CO1: Demonstrate plotting of lines in two and three dimensional space CO2: implementing appropriate codes for finding tangent vector and gradient vector CO3: Evaluate line and double integrals using sympy module CO4: Acquainting suitable commands for problems in applications of line and double integrals. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT551E - OPERATIONS RESEARCH USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: Operations research deals with the problems on optimization or decision making that are affected by certain constraints / restrictions in the environment. This course aims to enhance programming skills in Python to solve problems chosen from Operations Research.
Course objectives: This course will help the learner to COBJ1. gain a familiarity in using Python to solve linear programming problems, calculate the estimates that characteristics the queues and perform desired analysis on a network. COBJ2. use Python for solving problems on Operations Research. |
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Learning Outcome |
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CO1: On successful completion of the course, the students should be able to use Python programming to solve linear programming problems by using simplex method and dual simplex method. CO2: On successful completion of the course, the students should be able to solve Transportation Problems and Assignment Problems using Python module. CO3: On successful completion of the course, the students should be able to demonstrate competence in using Python modules to solve M/M/1, M/M/c queues, and Computations on Networks. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT581 - INTERNSHIP (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:0 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course provide the students an opportunity to gain work experience in the relevant institution / industry, connected to their subject of study. The experience gained in the workplace will give the students a competitive edge in their career.
Course Objective: This course help the learner to COBJ1. get exposed the work ethics of the field of their professional interest COBJ2. gain practical experience on the field of their interest COBJ3. choose their career through practical experience
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Learning Outcome |
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CO1: be competent in the field of their professional interest.
CO2: strengthen/upgrade the knowledge base required for handling problems during work
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA531 - LINEAR REGRESSION MODELS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course deals with simple and multiple linear regression models with their assumptions, estimation and their significance of regression coefficients. Model and variable selection techniques and variable transformation techniques are discussed. |
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Learning Outcome |
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CO1: Demonstrate simple and multiple regression analysis with one dependent and one or more independent variables. CO2: Infer about r-square, adjusted r-square for model selection. CO3: Apply the concepts of forward, backward and stepwise methods for selecting the independent variables. CO4: Demonstrate the concepts of heteroscedasticity, multicollinearity, autocorrelation and residual plots. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA541A - SAMPLING TECHNIQUES (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course designed to introduce about official statistical system in India and to understand the concepts of basic Sample survey designs. |
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Learning Outcome |
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After completion of this course the students will be able to 1. Demonstrate the basic principles and different steps in planning a sample survey. 2. Analysis various sampling techniques and their application 3. Demonstrate the official Statistical System in India. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA541B - DESIGN OF EXPERIMENTS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course introduces various experimental designs, selection of appropriate designs in planning a scientific experimentation. |
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Learning Outcome |
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CO1: CO1 Demonstrate the concepts of Analysis of Variance with comparison of more than two treatment. CO2: Apply the concepts of ANCOVA to compare the efficiency of various designs. CO3: Demonstrate the applications of factorial experiments with confounding. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA541C - ACTUARIAL STATISTICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course is designed to introduce the application of statistical methods in framing the insurance policies. |
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Learning Outcome |
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CO1: Demonstrate the principle terms used and major life insurance covered by Indian life insurance.
CO2: Infer the calculation of premium for various life insurance policies. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA541D - INTRODUCTION TO SPATIAL STATISTICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course designed as an application of statistics in geographical data analysis |
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Learning Outcome |
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CO1: Demonstrate the basic biological concepts in genetics
CO2: Infer the bioassays and their types CO3: Demonstrate the Feller?s theorem and dose response estimation using regression models and dose allocation schemes. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA551 - LINEAR REGRESSION MODELS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The course is designed to provide a practical exposure to the students in Simple and Multiple linear Regression Analysis. |
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Learning Outcome |
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CO1: Demonstrate the fitting of linear regression models for the real time data CO2: Infer model adequacy through various model selection process. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA552A - SAMPLING TECHNIQUES PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The course is designed to provide a practical exposure to the students in application of different sampling techniques. |
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Learning Outcome |
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CO1: After completion of this course the students will acquire the knowledge on different sampling techniques CO2: After completion of this course the students will able to decide the application of different sampling techniques under different situation. CO3: After completion of this course the students will be able to design sampling procedures for various situations |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA552B - DESIGN OF EXPERIMENTS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The course is designed to provide a practical exposure to the students for the various experimental designs. |
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Learning Outcome |
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CO1: Demonstrate the construction and analyses of various experimental designs using R programming. CO2: Demonstrate the efficiencies of various designs using R |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA552C - ACTUARIAL STATISTICS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The course is designed to provide a practical exposure to the students in Actuarial Modeling. |
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Learning Outcome |
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CO1: To develop a deeper understanding of the premium and risk calculations of life insurance policies. CO2: To implement actuarial statistics in real life CO3: To construct new models using real-life concepts |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA552D - SPATIAL STATISTICS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course is designed to teach practical Spatial problems using statistical softwares. |
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Learning Outcome |
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CO1: Demonstrate practically evaluate Spatial Statistical models using R programming. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
ECO631 - INTRODUCTION TO ECONOMETRICS (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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The objective of this course is to provide the basic knowledge of econometrics that is essential equipment for any economist. The course is designed to impart the learning of principles of econometric methods and tools. This is expected to improve student’s ability to understand of econometrics in the study of economics and finance. |
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Learning Outcome |
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CO1: Develop simple and multiple regression models and get acquainted with some advanced linear models and applying regression analysis to real-world economic examples and data sets.
CO2: Understand the different methods of econometric analysis, estimation and understanding the area of their application in economics.
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Text Books And Reference Books: | ||
Essential Reading / Recommended Reading | ||
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | ||
ECO641A - ENVIRONMENTAL ECONOMICS (2021 Batch) | ||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Learning Outcome |
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CO1: Explain how economics principles and tools can be used to analyse significance of the environment for the economy CO2: Describe the potential for market and government mechanisms to address environmental issues CO3: Conduct environmental valuation using any of the standard techniques studied in the course |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
ECO641B - FINANCIAL ECONOMICS (2021 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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This course introduces students to the conceptual and practical operations of the financial markets, institutions, and instruments network in the Indian context. The course is intended to provide an in-depth understanding of the operational issues of capital and money market network along with its regulatory framework.
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Learning Outcome |
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CO1: Demonstrate knowledge and understanding of financial market operations, regulations, instruments of primary, secondary markets and its impact on the economy CO2: Solve typical problems related to asset pricing, risk-return trade-off, equity valuation, and bond valuation using excel and evaluate company's stock performance using real-life data from online sources CO3: Develop the capacity to raise critical questions, debate on impact of current events taking place in the financial market and economy as a whole
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT631 - COMPLEX ANALYSIS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course description: This course enables the students to understand the basic theory and principles of complex analysis. COBJ1. understand the theory and geometry of complex numbers. COBJ2. evaluate derivatives and integrals of functions of complex variables. COBJ3. examine the transformation of functions of complex variables. COBJ4. obtain the power series expansion of a complex valued function. |
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Learning Outcome |
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CO 1: understand the concepts of limit, continuity, differentiability of complex functions. CO 2: evaluate the integrals of complex functions using Cauchy?s Integral Theorem/Formula and related results. CO 3: examine various types of transformation of functions of complex variables. CO 4: demonstrate the expansions of complex functions as Taylor, Power and Laurent Series, Classify singularities and poles. CO 5: apply the concepts of complex analysis to analyze and address real world problems. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT641A - MECHANICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course description: This course aims at introducing the basic concepts in statistics as well as dynamics of particles and rigid bodies; develop problem solving skills in mechanics through various applications. Course objectives: This course will help the learner to COBJ1. Gain familiarity with the concepts of force, triangular and parallelogram laws and conditions of equilibrium of forces. COBJ2. Analyse and interpret the Lamis Lemma and the resultant of more than one force. COBJ3. examine dynamical aspect of particles and rigid bodies. COBJ4. illustrate the concepts of simple harmonic motion and projectiles
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Learning Outcome |
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CO1: Compute resultant and direction of forces and examine the equilibrium of a force. CO2: Apply Lamis's Theorem and Varignon's Theorem in solving problems. CO3: Analyse the motion of a particle on a smooth surface. CO4: Discuss the motion of a particles subjected to Simple Harmonic Motion and fundamental concepts Projectiles. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT641B - NUMERICAL METHODS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course description: To explore the complex world problems physicists, engineers, financiers and mathematicians require certain methods. These practical problems can rarely be solved analytically. Their solutions can only be approximated through numerical methods. This course deals with the theory and application of numerical approximation techniques.
Course objectives: This course will help the learner COBJ1. To learn about error analysis, solution of nonlinear equations, finite differences, interpolation, numerical integration and differentiation, numerical solution of differential equations, and matrix computation. COBJ2. It also emphasis the development of numerical algorithms to provide solutions to common problems formulated in science and engineering. |
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Learning Outcome |
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CO1: Understand floating point numbers and the role of errors and its analysis in numerical methods. CO2: Derive numerical methods for various mathematical operations and tasks, such as interpolation, differentiation, integration, the solution of linear and nonlinear equations, and the solution of differential equations. CO3: Apply numerical methods to obtain approximate solutions to mathematical problems. CO4: Understand the accuracy, consistency, stability and convergence of numerical methods |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT641C - DISCRETE MATHEMATICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course description: It is a fundamental course in combinatorics involving set theory, permutations and combinations, generating functions, recurrence relations and lattices. Course objectives: This course will help the learner to COBJ 1: Gain a familiarity with fundamental concepts of combinatorial mathematics. COBJ 2: Understand the methods and problem solving techniques of discrete mathematics COBJ 3: Apply knowledge to analyze and solve problems using models of discrete mathematics |
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Learning Outcome |
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CO1: Enhance research, inquiry, and analytical thinking abilities. CO2: Apply the basics of combinatorics in analyzing problems. CO3: Enhance problem-solving skills. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT641D - NUMBER THEORY (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: This course is an introduction to elementary topics of analytical number theory. Topics such as divisibility, congruences and number-theoretic functions are discussed in this course. Some of the applications of these concepts are also included. Course Objectives: This course will help the learner to COBJ 1: Engage in sound mathematical thinking and reasoning. COBJ 2: Analyze, evaluate, or solve problems for given data or information. COBJ 3: Understand and utilize mathematical functions and empirical principles and processes. COBJ 4: Develop critical thinking skills, communication skills, and empirical and quantitative skills. |
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Learning Outcome |
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CO1: effectively express the concepts and results of number theory. CO2: understand the logic and methods behind the proofs in number theory. CO3: solve challenging problems in number theory. CO4: present specific topics and prove various ideas with mathematical rigour. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT641E - FINANCIAL MATHEMATICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description:Financial Mathematics deals with the solving of financial problems by using Mathematical methods. This course aims at introducing the basic ideas of deterministic mathematics of finance. The course focuses on imparting sound knowledge on elementary notions like simple interest, complex interest (annual and non-annual), annuities (varying and non-varying), loans and bonds. Course objectives: This course will help the learner to COBJ 1: gain familiarity in solving problems on Interest rates and Level Annuitiesd COBJ 2: derive formulae for different types of varying annuities and solve its associated problems COBJ 3: gain in depth knowledge on Loans and Bonds and hence create schedules for Loan Repayment and Bond Amortization Schedules. |
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Learning Outcome |
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CO1: On successful completion of the course, the students should be able to deal with the elementary notions like simple interest, compound interest and Annuities. CO2: On successful completion of the course, the students should be able to solve simple problems on interest rates, annuities, varying annuities, non-annual interest rates, loans and bonds. CO3: On successful completion of the course, the students should be able to apply the formulae appropriately in solving problems that mimics real life scenario. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT651 - COMPLEX ANALYSIS USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course will enable students to have hands on experience in constructing analytic functions, verifying harmonic functions, illustrating Cauchy’s integral theorem and bilinear transformations and in illustrating different types of sequences and series using Python. Course Objectives: This course will help the learner to COBJ 1:Python language using jupyter interface COBJ 2:Solving basic arithmetic problems using cmath built-in commands COBJ 3:Solving problems using cmath. |
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Learning Outcome |
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CO 1: acquire proficiency in using Python and cmath functions for processing complex numbers. CO 2: skilful in using Python modules to implement Milne-Thompson method. CO 3: expertise in illustrating harmonic functions and demonstrating Cauchy?s integral theorem Representation of conformal mappings using Matplotlib. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT651A - MECHANICS USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course aims at enabling the students to explore and study the statics and dynamics of particles in a detailed manner using Python. This course is designed with a learner-centric approach wherein the students will acquire mastery in understanding mechanics using Python. Course objectives: This course will help the learner to COBJ 1: Acquire skill in usage of suitable functions/packages of Python. COBJ 2: Gain proficiency in using Python to solve problems on Mechanics. |
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Learning Outcome |
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CO1: Acquire proficiency in using different functions of Python to study Differential Calculus. Mechanics. CO2: Demonstrate the use of Python to understand and interpret the dynamical aspects of Python. CO3: Use Python to evaluate the resultant of forces and check for equilibrium state of the forces. CO4: Be familiar with the built-in functions to find moment and couple. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT651B - NUMERICAL METHODS USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course will help the students to have an in depth knowledge of various numerical methods required in scientific and technological applications. Students will gain hands on experience in using Python for illustrating various numerical techniques. Course Objectives: This course will help the learner to COBJ 1: Develop the basic understanding of numerical algorithms and skills to implement algorithms to solve mathematical problems using Python. COBJ 2: To develop the basic understanding of the applicability and limitations of the techniques. |
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Learning Outcome |
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CO1: Implement a numerical solution method in a well-designed, well-documented Python program code. CO2: Interpret the numerical solutions that were obtained in regard to their accuracy and suitability for applications CO3: Present and interpret numerical results in an informative way. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT651C - DISCRETE MATHEMATICS USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course description: This course aims at providing hands on experience in using Python functions to illustrate the notions of combinatorics, set theory and relations. Course objectives: This course will help the learner to COBJ1. Gain a familiarity with programs on fundamental concepts of Combinatorial Mathematics COBJ2. Understand and apply knowledge to solve combinatorial problems using Python |
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Learning Outcome |
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CO1: Attain sufficient skills in using Python functions CO2: Demonstrate programming skills in solving problems related to applications of computational mathematics. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT651D - NUMBER THEORY USING PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course will help the students to gain hands-on experience in using Python for illustrating various number theory concepts such as the divisibility, distribution of primes, number conversions, congruences and applications of number theory. Course Objectives: This course will help the learner to COBJ 1: Be familiar with the built- in functions required to deal with number theoretic concepts and operations. COBJ 2: Develop programming skills to solve various number theoretic concepts. COBJ 3: Gain proficiency in symbolic computation using python. |
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Learning Outcome |
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CO1: to solve problems in number theory, number conversions. CO2: to demonstrate the understanding of number theory concepts. CO3: to model and solve practical problems using number theoretic concepts. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT651E - FINANCIAL MATHEMATICS USING EXCEL AND PYTHON (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: The course aims at providing hands on experience in using Excel/Python programming to illustrate the computation of constant/varying force of interest, continuously payable varying/non-varying annuities, increasing/decreasing annuity immediate/due, loans and bonds. Course objectives: This course will help the learner to COBJ 1: acquire skill in solving problems on Financial Mathematics using Python. COBJ 2: gain proficiency in using the Python programming skills to solve problems on Financial Mathematics. |
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Learning Outcome |
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CO1: demonstrate sufficient skills in using Python programming language for solving problems on Financial Mathematics. CO2: apply the notions on various types of interests, annuities, loans and bonds, by solving problems using Python. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
MAT681 - PROJECT ON MATHEMATICAL MODELS (2021 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:150 |
Credits:5 |
Course Objectives/Course Description |
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Course description: The course aims at providing hands on experience in analyzing practical problems by formulating the corresponding mathematical models. Course objectives: This course will help the learner to COBJ1. Develop positive attitude, knowledge and competence for research in Mathematics |
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Learning Outcome |
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CO1: Demonstrate analytical skills. CO2: Apply computational skills in Mathematics |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA631 - TIME SERIES ANALYSIS AND FORECASTING TECHNIQUES (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course covers applied statistical methods pertaining to time series and forecasting techniques. Moving average models like simple, weighted and exponential are dealt with. Stationary time series models and non-stationary time series models like AR, MA, ARMA and ARIMA are introduced to analyse time series data. |
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Learning Outcome |
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CO1: Demonstrate the approach and analyze univariate time series CO2: Infer the difference between various time series models like AR, MA, ARMA and ARIMA models CO3: Apply the various forecasting techniques to predict the future observations for real time data. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA641A - APPLIED STATISTICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course is designed to teach demographic methods, mortality and fertility rates, concept of index numbers and their usages are explained. Demand analysis helps students to understand the various statistical tools used in demand and supply sector. Educational and psychological statistics are used to emphasize the usage of statistics in real life. |
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Learning Outcome |
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CO1: Demonstrate the demographic profiles, mortality and fertility rates. CO2: Infer the concepts of Demand and supply and their importance
CO3: Demonstrate the importance of index numbers and their usage.Demonstrate the importance of index numbers and their usage. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA641B - STATISTICAL QUALITY CONTROL (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course is designed to introduce the application of statistical tools on industrial environment to study, analyze and control the quality of products. |
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Learning Outcome |
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CO1: Demonstrate the concepts control charts and sampling plans to improve the quality standards of the products. CO2: Apply the idea of Reliability theory to control the quality of industrial outputs.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA641C - BIOSTATISTICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course is designed as an application of statistics in medical sciences. The concepts of bioassays, quantitative epidemiology and survival analysis are introduced. R programming is used to analyze the biomedical data. |
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Learning Outcome |
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CO1: Demonstrate the basic biological concepts in Statistical genetics
CO2: Infer the bioassays, dose-response estimation, and dose-allocation schemes
CO3: Demonstrate the concepts in epidemiology and design and analysis of epidemiological studies. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA641D - STATISTICAL GENETICS (2021 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course is designed to introduce the basic concepts of genetics,estimation of linkage, Application and extension of the equilibrium law under different situation.This course also introduces the concept of inbreeding, Heritability, Repeatability and Geneticcorrelationin large populations. |
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Learning Outcome |
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CO1: Demonstrate the basic concepts of genetics and their applications. CO2: Demonstrate Fisher's fundamental theorem of natural selection with different forces. CO3: Demonstrate methods of estimation of Heritability, Repeatability and Genetic correlation. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA651 - TIME SERIES ANALYSIS AND FORECASTING TECHNIQUES PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
|
The course is designed to provide a practical exposure to the students in Time Series analysis |
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Learning Outcome |
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CO1: Demonstrate the analyses of univariate time series for real time data CO2: Forecast the future values of a given univariate time series. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA652A - APPLIED STATISTICS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course is designed to teach practical problems in demographic methods,Demand analysis, indexnumbers and educational statistics. |
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Learning Outcome |
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CO1: Demonstrate and evaluate demographic profiles, calculate various index numbers.
CO2: Apply concepts of Psychological and educational statistics for real life problems. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA652B - STATISTICAL QUALITY CONTROL PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
|
The course is designed to provide a practical exposure to the students for the various statistical quality control tools. |
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Learning Outcome |
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CO1: Demonstrate the variable and attribute control charts for industrial data
CO2: Demonstrate the sampling plans using R programming/EXCEL.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA652C - BIOSTATISTICS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
|
This course is designed to teach practical bio statistical problems using statistical softwares. |
|
Learning Outcome |
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CO1: Demonstrate and evaluate bio statistical models using R programming. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks | |
STA652D - STATISTICAL GENETICS PRACTICAL (2021 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
|
This course is designed to teach practical biostatistical problems using statistical softwares. |
|
Learning Outcome |
|
CO1: Demonstrate and evaluate bio statistical models using R programming. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern CIA I : 20 marks CIA II (Mid semester Exam) : 50 Marks CIA III : 20 Marks End Semester Examination : 100 Marks |