Department of
COMPUTER-SCIENCE






Syllabus for
Bachelor of Science (Computer Science, Mathematics, Statistics)
Academic Year  (2020)

 
1 Semester - 2020 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
CSC131 PROGRAMMING USING C AND DIGITAL COMPUTER FUNDAMENTALS 4 4 100
CSC151 C PROGRAMMING LAB 2 2 50
ENG121 ENGLISH - I 3 2 100
FRN121 FRENCH 3 3 100
MAT131 DIFFERENTIAL CALCULUS 4 4 100
MAT151 DIFFERENTIAL CALCULUS USING MAXIMA 2 2 50
STA131 DESCRIPTIVE STATISTICS AND PROBABILITY THEORY 4 4 100
STA151 DESCRIPTIVE STATISTICS AND PROBABILITY PRACTICAL 2 2 50
2 Semester - 2020 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
CSC231 DATA STRUCTURES AND OPERATING SYSTEMS 4 4 100
CSC251 DATA STRUCTURES LAB 2 2 50
ENG221 ENGLISH - II 3 2 100
FRN221 FRENCH 3 3 100
MAT231 DIFFERENTIAL EQUATIONS 4 4 100
MAT251 DIFFERENTIAL EQUATIONS USING MAXIMA 2 2 50
STA231 STATISTICAL METHODS 4 4 100
STA232 R PROGRAMMING 4 4 100
STA251 STATISTICAL METHODS PRACTICAL 2 2 50
3 Semester - 2019 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
AEN321 ADDITIONAL ENGLISH 3 3 100
CSC331 DATABASE MANAGEMENT SYSTEM AND JAVA PROGRAMMING 4 4 100
CSC351 JAVA PROGRAMMING LAB 2 2 50
ENG321 ENGLISH-III 3 3 100
FRN321 FRENCH 3 3 100
HIN321 HINDI 3 2 50
KAN321 KANNADA 3 03 100
MAT331 REAL ANALYSIS 4 4 100
MAT351 INTRODUCTION TO PYTHON PROGRAMMING FOR MATHEMATICS 2 2 50
STA331 STATISTICAL INFERENCE 4 4 100
STA332 APPLIED EXCEL 4 4 100
STA351 STATISTICAL INFERENCE PRACTICAL 2 2 50
4 Semester - 2019 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
AEN421 ADDITIONAL ENGLISH 3 3 100
CSC431 SOFTWARE ENGINEERING AND COMPUTER NETWORKS 4 4 100
CSC451 WEB TECHNOLOGY LAB 2 2 50
ENG421 ENGLISH-IV 3 3 100
FRN421 FRENCH 3 3 100
HIN421 HINDI 3 2 50
KAN421 KANNADA 3 03 100
MAT431 ALGEBRA 4 4 100
MAT451 INTRODUCTION TO MATHEMATICAL MODELLING USING PYTHON 2 2 50
STA431 SAMPLING TECHNIQUES 4 4 100
STA451 SAMPLING TECHNIQUES PRACTICAL 2 2 50
5 Semester - 2018 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
CSC541A DATA ANALYTICS 3 3 100
CSC541B INTERNET OF THINGS 3 3 100
CSC541C DIGITAL IMAGE PROCESSING 3 3 100
CSC541D BUSINESS INTELLIGENCE 3 3 100
CSC542A UNIX OPERATING SYSTEM 3 3 100
CSC542B PYTHON PROGRAMMING 3 3 100
CSC542D GRAPHICS AND ANIMATION 3 3 100
CSC542E .NET TECHNOLOGY 3 3 100
CSC551A DATA ANALYTICS LAB 2 2 50
CSC551B INTERNET OF THINGS LAB 2 2 50
CSC551C DIGITAL IMAGE PROCESSING LAB 2 2 50
CSC551D BUSINESS INTELLIGENCE LAB 2 2 50
CSC552A UNIX OPERATING SYSTEM LAB 2 2 50
CSC552B PYTHON PROGRAMMING LAB 2 2 50
CSC552D GRAPHICS AND ANIMATION LAB 2 2 50
CSC552E .NET TECHNOLOGY LAB 2 2 50
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
STA531 LINEAR REGRESSION MODELS 3 3 100
STA541A STATISTICAL QUALITY CONTROL 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 STATISTICAL QUALITY CONTROL 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 - 2018 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
CSC631 DESIGN AND ANALYSIS OF ALGORITHMS 3 3 100
CSC641A INTRODUCTION TO SOFT COMPUTING 3 3 100
CSC641B CLOUD COMPUTING 3 3 100
CSC641C COMPUTER ARCHITECTURE 3 3 100
CSC641D OOAD USING UML 3 3 100
CSC641E USER EXPERIENCE DESIGN(UX) 3 3 100
CSC681 MAIN PROJECT 4 04 100
MAT631 COMPLEX ANALYSIS 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 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 ELEMENTS OF STOCHASTIC PROCESS 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 ELEMENTS OF STOCHASTIC PROCESS PRACTICAL 2 2 50
STA652C BIOSTATISTICS PRACTICAL 2 2 50
STA652D STATISTICAL GENETICS PRACTICAL 2 2 50
        

          

  

Assesment Pattern

Exam pattern for theory

Component

Marks

CIA I

10

Mid Semester Examination (CIA II)

25

CIA III

10

Attendance

05

End Semester Exam

50

Total

100

Exam Pattern for practical

Component

Points

CIA of experiments

80

Test 1

25

Test 2

35

Viva-Voce Exam

10

Total

150

                  Total Marks : 50

Examination And Assesments
  • Continuous Internal assessment (CIA) forms 50% and the end semester examination forms the other 50% of the marks in both theory and practical.
  • The MSE & ESE for each theory paper is of two and three hours respectively.
  • The CIA for the practical sessions are done on a day-to-day basis depending upon their performance in the pre-lab, the conduct of the experiment, viva questions etc. Only those who qualify with minimum require attendance and CIA will be allowed to appear for the ESE.
Department Overview:
Department of Computer Science of CHRIST(Deemed to be University) strives to shape outstanding computer professionals with ethical and human values to reshape nation?s destiny. The training imparted aims to prepare young minds for the challenging opportunities in the IT industry with a global awareness rooted in the Indian soil, nourished and supported by experts in the field. Department of Mathematics, CHRIST (Deemed to be University) is one of the oldest departments of the University, established in the year 1969. It offers programmes in Mathematics at the undergraduate level, post graduate level as well as M.Phil and Ph.D. It is equipped with the highly committed team of instructors having versatile experience in teaching, research and has a passion to explore and innovate. Department is committed to provide the quality education in Mathematics, facilitate the holistic development, encourage students for pursuing higher studies in mathematics and motivate students to uphold scientific integrity and objectivity in professional endeavors. Department of Statistics is committed to excellence in teaching and equipping students to become practicing statisticians. The main objectives of the department are: 1. To acquaint students with various statistical methods and their applications in different fields 2. To cultivate statistical thinking among students 3. To develop skills in handling complex problems in data analysis and research design 4. To prepare students for futu
Mission Statement:
Vission: EXCELLENCE AND SERVICE Mission(Computer science department): To develop IT professionals with ethical and human values. Mission(Department of Mathematics): To organize, connect, create and communicate mathematical ideas effectively, through 4D's; Dedication, Discipline, Direction and Determination. Mission:The department of Statistics is committed to excellence in teaching and equipping students to become practicing statisticians.
Introduction to Program:
Bachelor of Science (BSc - Computer Science, Mathematics ,Statistics) is a 3-year undergraduate triple main programme spread over six semesters. It is an interdisciplinary program aimed at fostering sound fundamentals in computer science, mathematics statistics. The curriculum in computer science scales from imparting basic concepts in lower semesters to fine grain level along with electives in the higher semesters. Programming labs and projects strengthen the domain knowledge and exposure during the triple main course.The students are imparted both theoretical as well as practical knowledge in statistics using multiple statistical software. Mathematics: The undergraduate course in Mathematics is designed to enable the students to lay a strong foundation in various fields of Mathematics. The course enables the students to develop a respectable intellectual level seeking to expose the various concepts in Mathematics. It also aims at enhancing the students reasoning, analytical and problem solving skills. The first four semesters are devoted to appreciate the beauty of mathematics through Differential Calculus, Differential Equations, Real Analysis and Algebra. In order to help the students in exploration of mathematical concepts through activities and exploration, FOSS (Free and Open Source Software) tool MAXIMA and the computer language "Python" are introduced. Students find better perceptions of the classical courses like Linear Algebra, Complex Analysis and the elective co
Program Objective:
Programme Objective:The programme aims at providing theoretical and practical exposure to students to a varied range of statistical techniques in order to equip them to face the challenges of Industry and Higher Education. Programme Outcomes: On successful completions of the BSc Programme students will be able to PO1. Understand and apply the fundamental principles, concepts and methods in key areas of science and multidisciplinary fields PO2. Demonstrate problem solving, analytical and logical skills to provide solutions for the scientific requirements PO3. Develop the critical thinking with scientific temper PO4. Communicate the subject effectively PO5. Understand the importance and judicious use of technology for the sustainable growth of mankind in synergy with nature PO6. Understand the professional, ethical and social responsibilities PO7. Enhance the research culture and uphold the scientific integrity and objectivity PO8. Engage in continuous reflective learning in the context of technological and scientific advancements Programme Specific Outcomes: PSO1. Apply the theoretical concepts to design and develop software. PSO2. Demonstrate the problem solving skills in mathematical and digital sciences. PSO3. Provide a comprehensive understanding of Data Science and its applications. PSO4. Acquire a strong foundation in Statistical analytics PSO5. Express proficiency in oral and written communications to appreciate innovation in research. PSO6. Use sof

Assesment Pattern

CIA : 50%

ESE : 50%

Examination And Assesments

CIA : 50%

ESE : 50%

Department Overview:
Department of Computer Science of CHRIST(Deemed to be University) strives to shape outstanding computer professionals with ethical and human values to reshape nation?s destiny. The training imparted aims to prepare young minds for the challenging opportunities in the IT industry with a global awareness rooted in the Indian soil, nourished and supported by experts in the field. Department of Mathematics, CHRIST (Deemed to be University) is one of the oldest departments of the University, established in the year 1969. It offers programmes in Mathematics at the undergraduate level, post graduate level as well as M.Phil and Ph.D. It is equipped with the highly committed team of instructors having versatile experience in teaching, research and has a passion to explore and innovate. Department is committed to provide the quality education in Mathematics, facilitate the holistic development, encourage students for pursuing higher studies in mathematics and motivate students to uphold scientific integrity and objectivity in professional endeavors. Department of Statistics is committed to excellence in teaching and equipping students to become practicing statisticians. The main objectives of the department are: 1. To acquaint students with various statistical methods and their applications in different fields 2. To cultivate statistical thinking among students 3. To develop skills in handling complex problems in data analysis and research design 4. To prepare students for future cours
Mission Statement:
Vision and Mission: Vission: EXCELLENCE AND SERVICE Mission(Computer science department): To develop IT professionals with ethical and human values. Mission(Department of Mathematics): To organize, connect, create and communicate mathematical ideas effectively, through 4D's; Dedication, Discipline, Direction and Determination. Mission:The Department of Statistics is committed to excellence in teaching and equipping students to become practicing statisticians.
Introduction to Program:
Bachelor of Science (BSc - Computer Science, Mathematics , Statistics) is a 3-year undergraduate triple main programme spread over six semesters. It is an interdisciplinary program aimed at fostering sound fundamentals in computer science, mathematics statistics. The curriculum in computer science scales from imparting basic concepts in lower semesters to fine-grain level along with electives in the higher semesters. Programming labs and projects strengthen the domain knowledge and exposure during the triple main course. The students are imparted both theoretical as well as practical knowledge in statistics using multiple statistical software. Mathematics: The undergraduate course in Mathematics is designed to enable the students to lay a strong foundation in various fields of Mathematics. The course enables the students to develop a respectable intellectual level seeking to expose the various concepts in Mathematics. It also aims at enhancing the students reasoning, analytical, and problem-solving skills. The first four semesters are devoted to appreciate the beauty of mathematics through Differential Calculus, Differential Equations, Real Analysis and Algebra. In order to help the students in exploration of mathematical concepts through activities and exploration, FOSS (Free and Open Source Software) tool MAXIMA and the computer language "Python" are introduced. Students find better perceptions of the classical courses like Linear Algebra, Complex Analysis and elective cour
Program Objective:
Programme Objective:The programme aims at providing theoretical and practical exposure to students to a varied range of statistical techniques in order to equip them to face the challenges of Industry and Higher Education. Programme Outcomes: On successful completions of the BSc Programme students will be able to PO1. Understand and apply the fundamental principles, concepts and methods in key areas of science and multidisciplinary fields PO2. Demonstrate problem solving, analytical and logical skills to provide solutions for the scientific requirements PO3. Develop the critical thinking with scientific temper PO4. Communicate the subject effectively PO5. Understand the importance and judicious use of technology for the sustainable growth of mankind in synergy with nature PO6. Understand the professional, ethical and social responsibilities PO7. Enhance the research culture and uphold the scientific integrity and objectivity PO8. Engage in continuous reflective learning in the context of technological and scientific advancements Programme Specific Outcomes: PSO1. Apply the theoretical concepts to design and develop software. PSO2. Demonstrate the problem solving skills in mathematical and digital sciences. PSO3. Provide a comprehensive understanding of Data Science and its applications. PSO4. Acquire a strong foundation in Statistical analytics PSO5. Express proficiency in oral and written communications to appreciate innovation in research. PSO6. Use software effectively f

CSC131 - PROGRAMMING USING C AND DIGITAL COMPUTER FUNDAMENTALS (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course Objectives

The course provides the fundamentals of C programming, number systems, Boolean algebra and logic gates. The C programming helps the students to solve problems through logical thinking and digital logic helps the students to understand the concepts of constructing combinational and sequentialcircuits.

 

 

Learning Outcome

CO1: Understand the fundamentals of structured programming, number systems, Boolean algebra and logic gates

CO2: Learn to implement the concepts of arrays, functions, pointers, structures and to analyse logical expressions.

CO3: To create programs with ethical coding standards. CO4: To design combinational and sequential circuits.

 

Unit-1
Teaching Hours:6
Introduction
 

Algorithms - flowcharts- The C Character Set - Constants,  Variables and Keywords  -  Types of C Constants - Types of C Variables - Variable Names - C Instructions – data Type Declaration I/O instructions - Arithmetic Instruction - TypeConversion.

 

Unit-2
Teaching Hours:6
Control Structure
 

The Decision Control Structure - The if Statement- if-else Statement- Nested if-else Use of Logical Operators - ! Operator - Decisions Using switch - The Loop Control Structure While Loop - for Loop - break Statement - continue Statement- do-while Loop.

Unit-3
Teaching Hours:6
Arrays
 

A Simple Program Using Array -  Array Initialization - Two  Dimensional Arrays-  Initializing a 2-Dimensional Array - Memory Map of a 2-Dimensional Array – Strings - Standard Library String Functions - strlen( ) - strcpy( ) - strcat() - strcmp() - Two-Dimensional Array of Characters.

Unit-4
Teaching Hours:6
Functions & Pointers
 

Function - Passing Values between Functions - Scope Rule  of  Functions  -  Calling Convention - Return Type of Function - Call by Value and Call by Reference -  An  Introduction to Pointers - Pointer Notation –Recursion.

Unit-5
Teaching Hours:6
Macros and Structures
 

Introduction to macros, Structures - Declaring a Structure - Accessing Structure Elements - How Structure Elements areStored.

 

 

Unit-6
Teaching Hours:7
Introduction to Computers & Number systems
 

Different number systems and their conversions (Decimal, Binary, Octal and Hexadecimal) Binary arithmetic - Addition, subtraction, multiplication and division of binary numbers, 1’s and 2’s complement, Floating point numbers, Coding – BCD, Gray,ASCII

 

Unit-7
Teaching Hours:6
Boolean Algebra
 

Boolean operations and expressions, Laws and rules of boolean  algebra,  Demorgan’s Theorem, Boolean expressions, Simplification of Booleanexpression.

Unit-8
Teaching Hours:6
Logic Gates
 

OR gate, NOR gate , NOT gate , AND gate, NAND gate X-OR gate , X-NOR gate, The universal property of NOR and NAND gate, Karnaugh map (SOP).

Unit-9
Teaching Hours:5
Combinational logic
 

Adders (Half and Full), Decoder, Encoder, Multiplexer, De-Multiplexer  (Introductory ConceptsOnly).

 

Unit-10
Teaching Hours:6
Flip-Flops
 

 

Flip-flops- SR flip-flop, JK  flip-flop,  Master  slave  JK flip-flop,  Introduction to Registers  andCounters.

 

Text Books And Reference Books:

[1] Yashavant P. Kanetkar, Let Us C, 15th Edition, BPB Publications, 2012.

  [2] Floyd and Thomas L, Digital Computer Fundamentals, 11th Edition,  Pearson  International, 2015.

 

 

 

Essential Reading / Recommended Reading

[1]  Byron Gottfried and Jitender Chhabra, Programming with C, 3rd Ed, Tata McGrawHill, 2010.

[2]  Balagurusamy E, Programming in ANSI C, 4th Edition, Tata-McGraw-Hill, 2007.

[3]  Deitel H M and Deitel P J, C - How to Program, 7th Edition, Prentice-Hall, 2012.

[4]  Susant K Rout, Cimple,C, Tata-McGraw-Hill Publishing Company Ltd., 2016.

[5]     Malvino, Paul Albert, Leach, Donald P. Gautam Saha, Digital Principles And Applications, 7th Edition,TMH,2010.

[6]  Bartee, Thomas C, Digital Computer Fundamentals, 6th Edition, TMH,2010

Evaluation Pattern

CIA-50%

ESE-50%

CSC131N - PROGRAMMING USING C AND DIGITAL COMPUTER FUNDAMENTALS (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course Objectives

The course provides the fundamentals of C programming, number systems, Boolean algebra and logic gates. The C programming helps the students to solve problems through logical thinking and digital logic helps the students to understand the concepts of constructing combinational and sequentialcircuits.

 

 

Learning Outcome

CO1: Understand the fundamentals of structured programming, number systems, Boolean algebra and logic gates

CO2: Learn to implement the concepts of arrays, functions, pointers, structures and to analyse logical expressions.

CO3: To create programs with ethical coding standards. CO4: To design combinational and sequential circuits.

 

Unit-1
Teaching Hours:6
Introduction
 

Algorithms - flowcharts- The C Character Set - Constants,  Variables and Keywords  -  Types of C Constants - Types of C Variables - Variable Names - C Instructions – data Type Declaration I/O instructions - Arithmetic Instruction - TypeConversion.

 

Unit-2
Teaching Hours:6
Control Structure
 

The Decision Control Structure - The if Statement- if-else Statement- Nested if-else Use of Logical Operators - ! Operator - Decisions Using switch - The Loop Control Structure While Loop - for Loop - break Statement - continue Statement- do-while Loop.

Unit-3
Teaching Hours:6
Arrays
 

A Simple Program Using Array -  Array Initialization - Two  Dimensional Arrays-  Initializing a 2-Dimensional Array - Memory Map of a 2-Dimensional Array – Strings - Standard Library String Functions - strlen( ) - strcpy( ) - strcat() - strcmp() - Two-Dimensional Array of Characters.

Unit-4
Teaching Hours:6
Functions & Pointers
 

Function - Passing Values between Functions - Scope Rule  of  Functions  -  Calling Convention - Return Type of Function - Call by Value and Call by Reference -  An  Introduction to Pointers - Pointer Notation –Recursion.

Unit-5
Teaching Hours:6
Macros and Structures
 

Introduction to macros, Structures - Declaring a Structure - Accessing Structure Elements - How Structure Elements areStored.

 

 

Unit-6
Teaching Hours:7
Introduction to Computers & Number systems
 

Different number systems and their conversions (Decimal, Binary, Octal and Hexadecimal) Binary arithmetic - Addition, subtraction, multiplication and division of binary numbers, 1’s and 2’s complement, Floating point numbers, Coding – BCD, Gray,ASCII

 

Unit-7
Teaching Hours:6
Boolean Algebra
 

Boolean operations and expressions, Laws and rules of boolean  algebra,  Demorgan’s Theorem, Boolean expressions, Simplification of Booleanexpression.

Unit-8
Teaching Hours:6
Logic Gates
 

OR gate, NOR gate , NOT gate , AND gate, NAND gate X-OR gate , X-NOR gate, The universal property of NOR and NAND gate, Karnaugh map (SOP).

Unit-9
Teaching Hours:5
Combinational logic
 

Adders (Half and Full), Decoder, Encoder, Multiplexer, De-Multiplexer  (Introductory ConceptsOnly).

 

Unit-10
Teaching Hours:6
Flip-Flops
 

 

Flip-flops- SR flip-flop, JK  flip-flop,  Master  slave  JK flip-flop,  Introduction to Registers  andCounters.

 

Text Books And Reference Books:

[1] Yashavant P. Kanetkar, Let Us C, 15th Edition, BPB Publications, 2012.

  [2] Floyd and Thomas L, Digital Computer Fundamentals, 11th Edition,  Pearson  International, 2015.

 

 

 

Essential Reading / Recommended Reading

[1]  Byron Gottfried and Jitender Chhabra, Programming with C, 3rd Ed, Tata McGrawHill, 2010.

[2]  Balagurusamy E, Programming in ANSI C, 4th Edition, Tata-McGraw-Hill, 2007.

[3]  Deitel H M and Deitel P J, C - How to Program, 7th Edition, Prentice-Hall, 2012.

[4]  Susant K Rout, Cimple,C, Tata-McGraw-Hill Publishing Company Ltd., 2016.

[5]     Malvino, Paul Albert, Leach, Donald P. Gautam Saha, Digital Principles And Applications, 7th Edition,TMH,2010.

[6]  Bartee, Thomas C, Digital Computer Fundamentals, 6th Edition, TMH,2010

Evaluation Pattern

CIA-50%

ESE-50%

CSC151 - C PROGRAMMING LAB (2020 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The course introduces programming approach and practical implementation of theoretical concepts in C language. It provides the ability to understand, program, evaluate the given problems. The course also develops analyzing and problem solving skills based  on  C language.

 

 

 

Learning Outcome

CO1: Analyze and illustrate algorithm and flowchart for the given C program

CO2: Implement structured C programs

CO3: Trace and debug the programs written in C language

 

Unit-1
Teaching Hours:30
List of programs
 

 

1.  Program to implement conditional statements.

 

2.  Program to implement the concepts of while loop.

 

3.  Program implementing for loop concepts.

 

4.  Program to implement 1D array concept.

 

5.  Program based on string concepts.

 

6.  Program to implement string library functions.

 

7.  Program to implement 2D array concepts.

 

8.  Program to implement functions.

 

9.  Program demonstrating recursion functions.

 

10.Program to demonstrate call by value and call by reference.

 

 

Text Books And Reference Books:

[1] Yashavant P. Kanetkar, Let Us C, 15th Edition, BPB Publications, 2012.

 

 

Essential Reading / Recommended Reading

[1]  Byron Gottfried and Jitender Chhabra, Programming with C, 3rd Ed, Tata McGrawHill, 2010.

[2]  Balagurusamy E, Programming in ANSI C, 4th Edition, Tata-McGraw-Hill, 2007.

[3]  Deitel H M and Deitel P J, C - How to Program, 7th Edition, Prentice-Hall, 2012.

[4]  Susant K Rout, Cimple,C, Tata-McGraw-Hill Publishing Company Ltd., 2016.

 

 

 

Evaluation Pattern

CIA - 50%

ESE - 50%

CSC151N - C PROGRAMMING LAB (2020 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The course introduces programming approach and practical implementation of theoretical concepts in C language. It provides the ability to understand, program, evaluate the given problems. The course also develops analyzing and problem solving skills based  on  C language.

 

 

 

Learning Outcome

CO1: Analyze and illustrate algorithm and flowchart for the given C program

CO2: Implement structured C programs

CO3: Trace and debug the programs written in C language

 

Unit-1
Teaching Hours:30
List of programs
 

 

1.  Program to implement conditional statements.

 

2.  Program to implement the concepts of while loop.

 

3.  Program implementing for loop concepts.

 

4.  Program to implement 1D array concept.

 

5.  Program based on string concepts.

 

6.  Program to implement string library functions.

 

7.  Program to implement 2D array concepts.

 

8.  Program to implement functions.

 

9.  Program demonstrating recursion functions.

 

10.Program to demonstrate call by value and call by reference.

 

 

Text Books And Reference Books:

[1] Yashavant P. Kanetkar, Let Us C, 15th Edition, BPB Publications, 2012.

 

 

Essential Reading / Recommended Reading

[1]  Byron Gottfried and Jitender Chhabra, Programming with C, 3rd Ed, Tata McGrawHill, 2010.

[2]  Balagurusamy E, Programming in ANSI C, 4th Edition, Tata-McGraw-Hill, 2007.

[3]  Deitel H M and Deitel P J, C - How to Program, 7th Edition, Prentice-Hall, 2012.

[4]  Susant K Rout, Cimple,C, Tata-McGraw-Hill Publishing Company Ltd., 2016.

 

 

 

Evaluation Pattern

CIA - 50%

ESE - 50%

ENG121 - ENGLISH - I (2020 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:2

Course Objectives/Course Description

 
  • To expose learners to a variety of texts to interact with
  • To help learners classify ideologies and be able to express the same
  • To expose learners to visual texts and its reading formulas
  • To help learners develop a taste to appreciate works of literature through the organization of language
  • To help develop critical thinking
  • To help learners appreciate literature and the language nuances that enhances its literary values
  • To help learners understand the relationship between the world around them and the text/literature
  • To help learners negotiate with content and infer meaning contextually
  • To help learners understand logical sequencing of content and process information

·         To help improve their communication skills for larger academic purposes and vocational purposes

·         To enable learners to learn the contextual use of words and the generic meaning

·         To enable learners to listen to audio content and infer contextual meaning

·         To enable learners to be able to speak for various purposes and occasions using context specific language and expressions

·         To enable learners to develop the ability to write for various purposes using suitable and precise language.

Learning Outcome

·         Understand how to engage with texts from various countries, historical, cultural specificities and politics

 

·         Understand and develop the ability to reflect upon and comment on texts with various themes

 

·         Develop an analytical and critical bent of mind to compare and analyze the various literature they read and discuss in class

 

·         Develop the ability to communicate both orally and in writing for various purposes

 

Unit-1
Teaching Hours:6
language
 

Common errors- subject-verb agreement, punctuation, tense errors 

 

Unit-1
Teaching Hours:6
Unit 1 1. The Happy Prince By Oscar Wilde 2. Shakespeare Sonnet 18
 

Unit-2
Teaching Hours:6
language
 

sentence fragments, dangling modifiers, faulty parallelism,

Unit-2
Teaching Hours:6
unit 2
 

1. Why We Travel-Pico Iyer

2. What Solo Travel Has Taught Me About the World – and Myself -ShivyaNath- Blogpost

 

Unit-3
Teaching Hours:6
unit 3
 

1. Thinking Like a Mountain

By Aldo Leopold

2. Short Text: On Cutting a Tree

By Gieve Patel

Unit-3
Teaching Hours:6
language
 

Note taking

Unit-4
Teaching Hours:6
unit 4
 

1. Violence in the name of God is Violence against God

By Rev Dr Tveit

 

2. Poem: Holy Willie's Prayer

By Robert Burns

Unit-4
Teaching Hours:6
language
 

Paragraph writing

Unit-5
Teaching Hours:6
unit 5
 

1. The Story of B24

By Sir Arthur Conan Doyle

 2. Short Text: Aarushi Murder case 

 

Unit-5
Teaching Hours:6
Language
 

Newspaper report

Unit-6
Teaching Hours:6
unit 6
 

1.Long text:My Story- Nicole DeFreece

 

2. short text: Why You Should Never Aim for Six Packs

 

Unit-6
Teaching Hours:6
Language
 

Essay writing

Unit-7
Teaching Hours:6
Language
 

Paraphrasing and interpretation skills

Unit-7
Teaching Hours:6
unit 7
 

1.Long Text: Sir Ranjth Singh- Essay by SouravGanguly

2. Short text: Casey at the Bat-  Ernest Lawrence Thayer

Unit-8
Teaching Hours:3
visual text
 

Visual Text: Before the Flood

Text Books And Reference Books:

ENGlogue 1

Essential Reading / Recommended Reading

Addfitional  material as per teacher manual will be provided by the teachers

Evaluation Pattern

CIA 1=20

CIA 2=50 

CIA 3= 20 

ESE= 50 marks online and 50 marks written exam

ENG121N - ENGLISH - I (2020 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:2

Course Objectives/Course Description

 

ENGlogue is an English language course book for the students of first year of undergraduate courses studying in Christ University. The book that covers both Semesters I and II is built around fourteen contemporary themes, with each unit including two interesting and engaging reading texts. The texts are meant to trigger not just the desired language-learning behaviors but also to engage the students in thinking about various pertinent issues concerning the world around them. Each unit also includes teaching and tasks based on vocabulary, reading, writing and speaking. The overall objective of the book is to provide students with hands-on learning of language skills, equipping them not only for their immediate academic needs but also for their future professional careers.

  • To help learners classify ideologies and be able to express the same
  •  To expose learners to visual texts and its reading formulas
  • To help learners develop a taste to appreciate works of literature through the organization of language
  • To help develop critical thinking
  • To help learners appreciate literature and the language nuances that enhances its literary values
  • To help learners understand the relationship between the world around them and the text/literature
  • To help learners negotiate with content and infer meaning contextually
  • To help learners understand logical sequencing of content and process information
  • To help improve their communication skills for larger academic purposes and vocational purposes
  • To enable learners to learn the contextual use of words and the generic meaning
  • To enable learners to listen to audio content and infer contextual meaning
  • To enable learners to be able to speak for various purposes and occasions using context specific language and expression.
  •  To enable learners to develop the ability to write for various purposes using suitable and precise language.

Learning Outcome

  • Understand how to engage with texts from various countries, historical, cultural specificities and politics
  • Understand and develop the ability to reflect upon and comment on texts with various themes
  • Develop an analytical and critical bent of mind to compare and analyze the various literature they read and discuss in class.
  • Develop the ability to communicate both orally and in writing for various purposes.

Unit-1
Teaching Hours:6
Language
 

Common errors- subject-verb agreement, punctuation, tense errors

Unit-1
Teaching Hours:6
Beauty
 
  1. The Happy Prince By Oscar Wilde
  2. Sonnet 18 by Shakespeare
Unit-2
Teaching Hours:6
Language
 

Sentence fragments, dangling modifiers, faulty parallelism

Unit-2
Teaching Hours:6
Travel
 
  1. Why We Travel- Pico Iyer
  2. What Solo Travel Has Taught Me About the World and Myself - ShivyaNath
Unit-3
Teaching Hours:6
Environment
 
  1. Thinking Like a Mountain- Aldo Leopold
  2. On Cutting a Tree-  Gieve Patel

 

Unit-3
Teaching Hours:6
Language
 

Note taking

Unit-4
Teaching Hours:6
Language
 

Paragraph writing

Unit-4
Teaching Hours:6
Religion
 
  1. Violence in the name of God is Violence against God - Rev Dr Tveit
  2. Leave this Chanting and Singing and Telling of Beads- Rabindra Nath Tagore

 

Unit-5
Teaching Hours:6
Crime
 
  1. The Story of B24 by Sir Arthur Conan Doyle
  2.  Aarushi Murder case
Unit-5
Teaching Hours:6
Language
 

Newspaper report

Unit-6
Teaching Hours:6
Language
 

Essay writing

Unit-6
Teaching Hours:6
Health and Fitness
 
  1. My Story- Nicole DeFreece
  2. Why You Should Never Aim for Six Packs- Kinnari Jariwala
Unit-7
Teaching Hours:6
Language
 

Paraphrasing and interpretation skills

Unit-7
Teaching Hours:6
Sports
 
  1. Sir Ranjth Singh- Sourav Ganguly
  2. Casey at the Bat- Ernest Lawrence Thayer

 

Unit-8
Teaching Hours:3
Visual Text
 

Before the Flood

Text Books And Reference Books:

ENGlogue 1

Essential Reading / Recommended Reading

Additional material as per teacher manual will be provided by the teachers.

Evaluation Pattern

CIA 1=20

CIA 2=50

CIA 3= 20

ESE= 50 marks online and 50 marks written exam

FRN121 - FRENCH (2020 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

French as second language for the UG program

Learning Outcome

Enhancement of linguistic competencies and sharpening of written and oral communicative skills.

 

Unit-1
Teaching Hours:5
Chapter 1- I Discover
 

Lesson 1: Good Morning, How are you?

Unit-2
Teaching Hours:5
Chapter 1 - I discover
 

Lesson 2: Hello, My name is Agnes.

Unit-3
Teaching Hours:5
Chapter 2- Culture : Physical and Political france
 

Lesson 1: Who is it?

Unit-4
Teaching Hours:5
Chapter 2- Culture: Physical and Political France
 

Lesson 2: In my bag , I have......

Unit-5
Teaching Hours:5
Les Fables de la Fontaine
 

1. La cigale et la fourmis

Unit-6
Teaching Hours:5
Visual Text
 

A French Film 

Unit-7
Teaching Hours:5
Chapter 3- Viideo Workshop: He is cute!
 

Lesson 1 : How is he?

Unit-8
Teaching Hours:5
Les Fables de la Fontaine
 

2. Le renard et le corbeau

Unit-9
Teaching Hours:5
Chapter 3- Video Workshop: He is cute
 

Lesson 2: Hello?

Text Books And Reference Books:

1.      Cocton, Marie-Noelle. Génération A1. Paris : Didier, 2016 

2.      De Lafontaine, Jean. Les Fables de la Fontaine. Paris, 1668

 

Essential Reading / Recommended Reading

1. Thakker, Viral. Plaisir d’écrire. New Delhi : Langers International Pvt. Ltd., 2011

2. French websites like Bonjour de France, Fluent U French, Learn French Lab, Point du FLE etc.

Evaluation Pattern

 

Assessment Pattern

CIA (Weight)

ESE (Weight)

CIA 1 – Assignment & MOODLE Testing (Quiz)

10%

 

CIA 2 –Mid Sem Exam

25%

 

CIA 3 – Role Play / Theatre and DELF Pattern: Reading & Writing

10%

 

Attendance

05%

 

End Sem Exam

 

50%

Total

50%

50%

 

MAT131 - DIFFERENTIAL CALCULUS (2020 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 aims at enabling the students to know various concepts and principles of differential calculus and its applications.  Sound knowledge of calculus is essential for the students of mathematics for the better perceptions of the subject and its development.

Course objectives​: This course will help the learner to

COBJ1. Gain familiarity with the concepts of limit, continuity and differentiability.

COBJ2. Understand the relationship between the concepts of differentiability and continuity.

COBJ3. Analyse and interpret the different versions of mean value theorems.

COBJ4. Learn successive differentiation and nth derivative of product of two functions.

COBJ5. Find derivative of functions of more than one variable.

COBJ6. Be familiar with curve tracing.

Learning Outcome

On successful completion of the course, the students should be able to

CO1. Compute limits, derivatives and examine the continuity, differentiability of a function at a point.
CO2. Understand the properties of continuous functions and prove that differentiability implies continuity
CO3. Prove Mean value theorems and analyse its geometric interpretation.
CO4. Compute derivatives of any order and apply Leibniz’ theorem to find nth derivative of product of two functions.
CO5. Master the fundamental concepts of partial differentiation and apply Euler’s theorem for homogeneous functions.
CO6. Gain knowledge on the concepts such as asymptotes, concavity/convexity and singular points and apply the same for curve tracing.

Unit-1
Teaching Hours:20
Limits, Continuity, Differentiability and Mean Value Theorems
 

Definition of the limit of a function (ε-δ) form – Continuity, Uniform Continuity – Types of discontinuities – Properties of continuous functions on a closed interval - Boundedness theorem and extreme value theorem – Differentiability – Mean Value Theorems: Rolle’s theorem – Lagrange’s and Cauchy’s First Mean Value Theorems – Taylor’s theorem (Lagrange’s form and Cauchy’s forms of remainder) – Maclaurin’s theorem and expansions -Indeterminate forms. .

Unit-2
Teaching Hours:20
Successive and Partial Differentiation
 

Successive differentiation – nth derivatives of functions – Leibnitz theorem and its applications – Partial differentiation – First and higher order derivatives – Differentiation of homogeneous functions – Euler’s theorem – Taylor’s theorem for two variables (only statements and problems)- Maxima and Minima of functions of two variables.

Unit-3
Teaching Hours:20
Curve Tracing
 

Tangents and Normals, Concavity and convexity, Curvature, Asymptotes, Singular points, Tracing of curves (Parametric representation of curves and tracing of parametric curves, Polar coordinates and tracing of curves in polar coordinates)..

Text Books And Reference Books:

G.B. Thomas, M.D.Weir and J. Hass, ThomasCalculus, 12th ed., Pearson Education India, 2015. 

Essential Reading / Recommended Reading
  1. H. Anton, I. Birens and S. Davis, Calculus, John Wiley and Sons Inc., 2002.
  2. F. Ayres and E. Mendelson, Schaum's Outline of Calculus, 6th ed. USA: Mc. Graw Hill., 2013.
  3. J. Stewart, Single Variable Essential Calculus: Early Transcendentals, 2nd ed.: Belmont, USA: Brooks/Cole Cengage Learning., 2013.
  4. S. Narayanan & T. K. M. Pillay, Calculus, Reprint, India: S. Viswanathan Pvt. Ltd., 2009. (vol. I & II.)
  5. M. Spivak, Calculus, 3rd ed., Cambridge University Press, 2006.
  6. T.M. Apostol, Calculus, Vol-II, Wiley India Pvt. Ltd., 2011.
  7. J. Edwards, An elementary treatise on the differential calculus: with applications and numerous examples, Reprint, Charleston, USA: BiblioBazaar, 2010.
  8. N. P. Bali, Differential Calculus, New ed. New Delhi, India: Laxmi Publications (P) Ltd., 2012.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT131N - DIFFERENTIAL CALCULUS (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course aims at enabling the students to know various concepts and principles of differential calculus and its applications.  Sound knowledge of calculus is essential for the students of mathematics for the better perceptions of the subject and its development. 

 

Learning Outcome

CO1. Compute limits, derivatives and examine the continuity, differentiability of a function at a point.

CO2. Understand the properties of continuous functions and prove that differentiability implies continuity

CO3. Prove Mean value theorems and analyse its geometric interpretation.

CO4. Compute derivatives of any order and apply Leibniz’ theorem to find nth derivative of product of two functions.

CO5. Master the fundamental concepts of partial differentiation and apply Euler’s theorem for homogeneous functions.

CO6. Gain knowledge on the concepts such as asymptotes, concavity/convexity and singular points and apply the same for curve tracing.

Unit-1
Teaching Hours:20
Limits, Continuity, Differentiability and Mean Value Theorems
 

Definition of the limit of a function (ε-δ) form – Continuity, Uniform Continuity – Types of discontinuities – Properties of continuous functions on a closed interval – Differentiability – Mean Value Theorems: Rolle’s theorem – Lagrange’s and Cauchy’s First Mean Value Theorems – Taylor’s theorem (Lagrange’s form and Cauchy’s forms of remainder) – Maclaurin’s theorem and expansions -Indeterminate forms. - Maxima and Minima.

Unit-2
Teaching Hours:20
Successive and Partial Differentiation
 

Successive differentiation – nth derivatives of functions – Leibnitz theorem and its applications – Partial differentiation – First and higher order derivatives – Differentiation of homogeneous functions – Euler’s theorem – Taylor’s theorem for two variables (only statements and problems)- Maxima and Minima of functions of two variables.

Unit-3
Teaching Hours:20
Curve Tracing
 

Tangents and Normals, Curvature, Asymptotes, Singular points, Tracing of curves (Parametric representation of curves and tracing of parametric curves, Polar coordinates and tracing of curves in polar coordinates).

Text Books And Reference Books:

G.B. Thomas, M.D.Weir and J. Hass, ThomasCalculus, 12th ed., Pearson Education India, 2015.

 

Essential Reading / Recommended Reading

H. Anton, I. Birens and S. Davis, Calculus, John Wiley and Sons Inc., 2002.

F. Ayres and E. Mendelson, Schaum's Outline of Calculus, 6th ed. USA: Mc. Graw Hill., 2013.

J. Stewart, Single Variable Essential Calculus: Early Transcendentals, 2nd ed.: Belmont, USA: Brooks/Cole Cengage Learning., 2013.

S. Narayanan & T. K. M. Pillay, Calculus, Reprint, India: S. Viswanathan Pvt. Ltd., 2009. (vol. I & II.)

M. Spivak, Calculus, 3rd ed., Cambridge University Press, 2006.

T.M. Apostol, Calculus, Vol-II, Wiley India Pvt. Ltd., 2011.

J. Edwards, An elementary treatise on the differential calculus: with applications and numerous examples, Reprint, Charleston, USA: BiblioBazaar, 2010.

N. P. Bali, Differential Calculus, New ed. New Delhi, India: Laxmi Publications (P) Ltd., 2012.

Evaluation Pattern

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT151 - DIFFERENTIAL CALCULUS USING MAXIMA (2020 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 Differential Calculus Using wxMaxima is aimed at enabling the students to appreciate and understand core concepts of Differential Calculus with the help of the free and open source mathematical software Maxima. It is designed to gain hands on experience in using MAXIMA to perform plotting of standard curves, to find limits of a function, illustrate differentiability and solve applied problems on differentiation.

Course objectives​: This course will help the learner to

COBJ1. Acquire skill in solving problems on Differential Calculus using MAXIMA.
COBJ2. Gain proficiency in using MAXIMA to solve problems on Differential Calculus.

Learning Outcome

On successful completion of the course, the students should be able to  

CO1. Acquire proficiency in using MAXIMA to study Differential Calculus.
CO2. Demonstrate the use of MAXIMA to understand and interpret the core concepts of various types of functions from the algebraic and graphical points of view.
CO3. Use MAXIMA to evaluate limits of functions and check for continuity graphically as well as algebraically.
CO4. Be familiar with the built-in functions to find derivatives of any order and solve application problems dealing with the concept of rate of change.
CO5. Sketch graphs of standard curves using MAXIMA to interpret tracing of curves.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Introduction to MAXIMA
  2. Sketch the graph of various functions: explicit-implicit-parametric-polar.
  3. Evaluation of limits using built-in function in maxima and illustration of the same graphically.
  4. Demonstration of continuous functions and types of discontinuities.
  5. Determination of derivatives. - graphical interpretation of derivatives.
  6. Verification of mean value theorems.
  7. Evaluation of extreme points, maxima and minima.
  8. Calculation of nth derivatives of functions
  9. Partial differentiation of functions of two variables.
  10. Tracing of curves.
  11. Applications of differentiation
Text Books And Reference Books:
  1. Zachary Hannan, wxMaxima for Calculus I (Creative Commons Attribution-Non-Commercial-Share Alike 4.0 International), Solano Community College, Edition 1.0 Publisher, Published June 17, 2015.
  2. Zachary Hannan, wxMaxima for Calculus II (Creative Commons Attribution-Non-Commercial-Share Alike 4.0 International), Solano Community College, Edition 1.0 Publisher, Published June 17, 2015.
Essential Reading / Recommended Reading

 Sandeep Koranne, Handbook of Open Source Tools, Springer Science & Business Media, 2010.

Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.


Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

MAT151N - DIFFERENTIAL CALCULUS USING MAXIMA (2020 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The course Differential Calculus Using Maxima is aimed at enabling the students to appreciate and understand core concepts of Differential Calculus with the help of the free and open source mathematical software Maxima. It is designed to gain hands on experience in using MAXIMA to perform plotting of standard curves, to find limits of a function, illustrate differentiability and solve applied problems on differentiation.

Learning Outcome

CO1. Acquire proficiency in using MAXIMA to study Differential Calculus.

CO2. Demonstrate the use of MAXIMA to understand and interpret the core concepts various types of functions from the algebraic and graphical points of view.

CO3. Use MAXIMA to evaluate limits of functions and check for continuity graphically as well as algebraically.

CO4. Be familiar with the built-in functions to find derivatives of any order and solve application problems dealing with the concept of rate of change.

CO5. Sketch graphs of standard curves using MAXIMA to interpret tracing of curves.

Unit-1
Teaching Hours:30
Proposed Topics
 

1.      Introduction to MAXIMA

2.      Sketch the graph of various functions: explicit-implicit-parametric-polar.

3.      Evaluation of limits using built-in function in maxima and illustration of the same graphically.

4.      Demonstration of continuous functions and types of discontinuities.

5.      Determination of derivatives. - graphical interpretation of derivatives.

6.      Verification of mean value theorems.

7.      Evaluation of extreme points, maxima and minima.

8.      Calculation of nth derivatives of functions

9.      Partial differentiation of functions of two variables.

10.  Tracing of curves.

11.  Applications of differentiation

Text Books And Reference Books:

Zachary Hannan, wxMaxima for Calculus I (Creative Commons Attribution-Non-Commercial-Share Alike 4.0 International), Solano Community College, Edition 1.0 Publisher, Published June 17, 2015.

Zachary Hannan, wxMaxima for Calculus II (Creative Commons Attribution-Non-Commercial-Share Alike 4.0 International), Solano Community College, Edition 1.0 Publisher, Published June 17, 2015.

Essential Reading / Recommended Reading

Sandeep Koranne, Handbook of Open Source Tools, Springer Science & Business Media, 2010.

Evaluation Pattern

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

 

STA131 - DESCRIPTIVE STATISTICS AND PROBABILITY THEORY (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course is designed to introduce the historical development of statistics, presentation of data, descriptive measures and fitting mathematical curves for the data.
This course also introduces measurement of relationship of quantitative and qualitative data and the concept of probability.

 

Learning Outcome

CO1:Demonstrate the history of statistics and present the data in various forms.

CO2:Infer the concept of correlation and regression for relating two or more related variables.

CO3:Demonstrate the probabilities for various events. 

 

Unit-1
Teaching Hours:10
Organization and presentation of data
 


Origin and development of Statistics, Scope, limitation and misuse of statistics. Types of data:
primary, secondary, quantitative and qualitative data. Types of Measurements: nominal, ordinal,
discrete and continuous data. Presentation of data by tables: construction of frequency
distributions for discrete and continuous data, graphical representation of a frequency
distribution by histogram and frequency polygon, cumulative frequency distributions (inclusive
and exclusive methods).

Unit-2
Teaching Hours:15
Descriptive Statistics
 

Measures of location or central tendency: Arthimetic mean, Median, Mode, Geometric mean,
Harmonic mean. Partition values: Quartiles, Deciles and percentiles. Measures of dispersion:
Mean deviation, Quartile deviation, Standard deviation, Coefficient of variation. Moments:
measures of skewness, Kurtosis.

Unit-3
Teaching Hours:10
Correlation
 

Correlation: Scatter plot, Karl Pearson coefficient of correlation, Spearman's rank correlation coefficient, multiple and partial correlations (for 3 variates only). Regression: Concept of errors, Principles of Least Square, Simple linear regression and its properties. 

Unit-4
Teaching Hours:15
Basics of probability
 

Random experiment, sample point and sample space, event, algebra of events. Definition of Probability: classical, empirical and axiomatic approaches to probability, properties of probability. Theorems on probability, conditional probability and independent events, Laws of total probability, Baye’s theorem and its applications.

Unit-5
Teaching Hours:10
Association of attributes
 

Relation between class frequencies, consistency of data, independence of attributes, criterion of independence, association of attributes: Yule’s coefficient of association, Yule’coefficient of colligation.

Text Books And Reference Books:

1. Rohatgi V.K and Saleh E, An Introduction to Probability and Statistics, 3 rd edition, John
Wiley & Sons Inc., New Jersey, 2015.
2. Gupta S.C and Kapoor V.K, Fundamentals of Mathematical Statistics, 11 th edition, Sultan
Chand & Sons, New Delhi, 2014.

Essential Reading / Recommended Reading

1. Mukhopadhyay P, Mathematical Statistics, Books and Allied (P) Ltd, Kolkata, 2015.
2. Walpole R.E, Myers R.H, and Myers S.L, Probability and Statistics for Engineers and
Scientists, Pearson, New Delhi, 2017.
3. Montgomery D.C and Runger G.C, Applied Statistics and Probability for Engineers,
Wiley India, New Delhi, 2013.
4.  Agarwal B.L, Basic Statistics, 6th Edition, New Age International Publication, 2015.

Evaluation Pattern

Component

Marks

CIA I

10

Mid Semester Examination (CIA II)

25

CIA III

10

Attendance

05

End Semester Exam

50

Total

100

STA131N - DESCRIPTIVE STATISTICS AND PROBABILITY (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course is designed to introduce the historical development of statistics, presentation of data, descriptive measures and fitting mathematical curves for the data. This course also introduces measurement of relationship of quantitative and qualitative data and the concept of probability.

Learning Outcome

CO1:To enable the students understand and apply the descriptive measures and probability for data analysis.

 CO2: Implement theoritical concepts of descriptive measures and probability

Unit-1
Teaching Hours:10
Organization and presentation of data
 

Origin and development of Statistics, Scope, limitation and misuse of statistics. Types of data:

primary, secondary, quantitative and qualitative data. Types of Measurements: nominal, ordinal,

discrete and continuous data. Presentation of data by tables: construction of frequency

distributions for discrete and continuous data, graphical representation of a frequency

distribution by histogram and frequency polygon, cumulative frequency distributions (inclusive

and exclusive methods).

Unit-2
Teaching Hours:15
Descriptive Statistics
 

Measures of location or central tendency: Arthimetic mean, Median, Mode, Geometric mean,

Harmonic mean. Partition values: Quartiles, Deciles and percentiles. Measures of dispersion:

Mean deviation, Quartile deviation, Standard deviation, Coefficient of variation. Moments:

measures of skewness, Kurtosis

Unit-3
Teaching Hours:10
Correlation
 

Correlation: Scatter plot, Karl Pearson coefficient of correlation, Spearman's rank correlation coefficient, multiple and partial correlations (for 3 variates only).

Unit-4
Teaching Hours:15
Basics of probability
 

Random experiment, sample point and sample space, event, algebra of events. Definition of Probability: classical, empirical and axiomatic approaches to probability, properties of probability. Theorems on probability, conditional probability and independent events, Laws of total probability, Baye’s theorem and its applications.

Unit-5
Teaching Hours:10
Association of attributes
 

Relation between class frequencies, consistency of data, independence of attributes, criterion of independence, association of attributes: Yule’s coefficient of association, Yule’coefficient of colligation.

Text Books And Reference Books:

1. Rohatgi V.K and Saleh E, An Introduction to Probability and Statistics, 3 rd edition, John

Wiley & Sons Inc., New Jersey, 2015.

2. Gupta S.C and Kapoor V.K, Fundamentals of Mathematical Statistics, 11 th edition, Sultan

Chand & Sons, New Delhi, 2014.

Essential Reading / Recommended Reading

1. Mukhopadhyay P, Mathematical Statistics, Books and Allied (P) Ltd, Kolkata, 2015.

2. Walpole R.E, Myers R.H, and Myers S.L, Probability and Statistics for Engineers and

Scientists, Pearson, New Delhi, 2017.

3. Montgomery D.C and Runger G.C, Applied Statistics and Probability for Engineers,

Wiley India, New Delhi, 2013.

4. Mood A.M, Graybill F.A and Boes D.C, Introduction to the Theory of Statistics, McGraw

Hill, New Delhi, 2008.

Evaluation Pattern

Component                                          Marks

CIA I                                                      10

Mid Semester Examination (CIA II)           25

CIA III                                                    10

Attendance                                              05

End Semester Exam                                  50

Total                                                       100

STA151 - DESCRIPTIVE STATISTICS AND PROBABILITY PRACTICAL (2020 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 Basic concepts of Excel and different way of representation of data.

Learning Outcome

CO1:Understand data and analysis

CO2: Implement EXCEL in given data set

CO3: Create  a research statement and collect data related to the statement along with the representation of data and
practical exposure on DAP.

Unit-1
Teaching Hours:30
List of practical assignments
 

1.   1.      Questionnaire preparation, data collection and data base creation using Excel sheet

2.      Basic data manipulation techniques: sorting, filtering, conditional formatting 

3.      Pivot Table construction

4.      Diagrammatic representation

5.      Graphical representation

6.      Descriptive statistics using statistical functions

7.      Data Analysis Pack (DAP)

8.      Correlation and Correlation matrix

9.      Exercise on partial and multiple correlation coefficient.

10.  Regression analysis and their significance

11.  Linear Curve estimation

12.  Second order Polynomial Curve estimation

Text Books And Reference Books:

1.     Rohatgi V.K and Saleh E, An Introduction to Probability and Statistics, 3rd edition, John Wiley & Sons Inc., New Jersey, 2015.

2.     Gupta S.C and Kapoor V.K, Fundamentals of Mathematical Statistics, 11th edition, Sultan Chand & Sons, New Delhi, 2014.

Essential Reading / Recommended Reading

1.     Mukhopadhyay P, Mathematical Statistics, Books and Allied (P) Ltd, Kolkata, 2015.

2.     Walpole R.E, Myers R.H, and Myers S.L, Probability and Statistics for Engineers and Scientists, Pearson, New Delhi, 2017.

3.     Montgomery D.C and Runger G.C, Applied Statistics and Probability for Engineers, Wiley India, New Delhi, 2013.

4.     Mood A.M, Graybill F.A and Boes D.C, Introduction to the Theory of Statistics, McGraw Hill, New Delhi, 2008.

Evaluation Pattern

Section

Parameters

Marks

A

Objective/Aim

2

B

Analysis

3

C

Interpretation

3

D

Timely submission

2

Total

 

10

STA151N - DESCRIPTIVE STATISTICS AND PROBABILITY PRACTICAL (2020 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 Basic concepts of Excel and different way of representation of data.

Learning Outcome

CO1:Understand data and analysis

CO2: Implement EXCEL in given data set

CO3: Create  a research statement and collect data related to the statement along with the representation of data and practical exposure on DAP.

Unit-1
Teaching Hours:30
List of practical assignments
 

1.     Questionnaire preparation, data collection and data base creation using Excel sheet

2.     Basic data manipulation techniques: sorting, filtering, conditional formatting

3.     Pivot Table construction

4.     Diagrammatic representation

5.     Graphical representation

6.     Descriptive statistics using statistical functions and Data Analysis Pack (DAP)

7.     Exercise on correlation and Correlation matrix

8.     Exercise on partial and multiple correlation coefficients.

Text Books And Reference Books:

1.     Rohatgi V.K and Saleh E, An Introduction to Probability and Statistics, 3rd edition, John Wiley & Sons Inc., New Jersey, 2015.

 2.     Gupta S.C and Kapoor V.K, Fundamentals of Mathematical Statistics, 11th edition, Sultan Chand & Sons, New Delhi, 2014.

Essential Reading / Recommended Reading

1.     Mukhopadhyay P, Mathematical Statistics, Books and Allied (P) Ltd, Kolkata, 2015.

 2.     Walpole R.E, Myers R.H, and Myers S.L, Probability and Statistics for Engineers and Scientists, Pearson, New Delhi, 2017.

 3.     Montgomery D.C and Runger G.C, Applied Statistics and Probability for Engineers, Wiley India, New Delhi, 2013.

 4.     Mood A.M, Graybill F.A and Boes D.C, Introduction to the Theory of Statistics, McGraw Hill, New Delhi, 2008.

Evaluation Pattern

 

Section

Parameters

Marks

A

Objective/Aim

2

B

Analysis

3

C

Interpretation

3

D

Timely submission

2

Total

 

10

 

CSC231 - DATA STRUCTURES AND OPERATING SYSTEMS (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

The course provides knowledge on the data storage techniques, accessing techniques, the various operations applied on the data and fundamental knowledge of operating system architecture and the various operations performed by the Operating system. This course helps the students to attain comprehensive understanding of programming and to acquire the knowledge on the different tasks like job scheduling, memory  management,  file  handling done by operatingsystems.

Learning Outcome

CO1: Understand the different Data Structures using C and the fundamental principles of operating system and system structure.

CO2: To implement the different operations on the data structures and to evaluate the process scheduling, deadlock system and effective memory management

CO3: To analyse the applications of data structures in real time applications CO4: To analyse the file structure, directory structure and allocation methods.

Unit-1
Teaching Hours:6
Arrays
 

Introduction to data structures- Arrays- Introduction, Array  Operations,  linear  search  – Binary search – insertion in an array– deletion in an array – sort  – Bubble  Sort  - Insertion  Sort - SelectionSort.

Unit-2
Teaching Hours:6
Linked List
 

Introduction –Insertion – Deletion – Search - Double Linked List Representations.

Unit-3
Teaching Hours:6
Stack & Queue
 

Introduction - Stack Operations using arrays and linked lists - Infix to Prefix - Queue Operations using array and linkedlist.

Unit-4
Teaching Hours:6
Binary Trees
 

Introduction - Binary Trees- Properties of Binary Trees - Binary Tree  Representations  -  Binary TreeTraversals.

Unit-5
Teaching Hours:6
Graphs
 

Introduction – Definitions and terminology – graph representations – Depth first search – Breadth first search

Unit-6
Teaching Hours:6
Introduction and System Structures
 

Operating system definition, computer system organization, architecture, structure and operations, process, memory and storage management.

 

Unit-7
Teaching Hours:6
Process Management
 

Process concepts, scheduling, operations on processes. Process Scheduling: Basic concepts, scheduling criteria, scheduling algorithms, Synchronization: Background, critical section problems.

Unit-8
Teaching Hours:6
Deadlock
 

Deadlock System model, deadlock characterization, methods for handling deadlock, deadlock prevention, avoidance and detection.

Unit-9
Teaching Hours:6
Memory Management
 

Memory Management Strategies: Background, swapping, Memory allocation,  Paging, Structure of the pagetable.

Unit-10
Teaching Hours:6
File system
 

File system structure, directory structure, allocation methods and free-space management.

Self Learning : Segmentation, File system structure.

Text Books And Reference Books:

[1]   Silberschatz, P.B. Galvin and G. Gagne, Operating System  Concepts,  9th  Edition, New Delhi, Wiley India,2012.

Essential Reading / Recommended Reading

[1]    William Stallings, Operating system Internals and Design Principles, 7th Edition, Prentice Hall,2017.

[2]    Andrew S. Tanenbaum and Herbert Bos, Modern Operating Systems, 4th Edition, Pearson,2014.

[3]    H.M. Deitel, P. J. Deitel, D. R. Choffnes, Operating Systems, 3rd Edition, Pearson, 2007.

Evaluation Pattern

50% ESE + 50% CIA

CSC251 - DATA STRUCTURES LAB (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The course introduces programming approach and practical implementation of data structure concepts. The course aims to familiarize with practical and real time application of linear and Non-linear data structure. It provides the ability to identify, apply and evaluate relevant data structure concept for the given problems.

Learning Outcome

Upon completion of the course students will be able to:

CO1: Understand the need for Data Structures when building application

CO2: To write diversified solutions for given problem

CO3: Improve logical, analytical, problem solving skill using Cprogramming

 

Unit-1
Teaching Hours:30
List of lab Programs
 

1.            Inserting an element into one dimensionalarray

2.            Deletion of an element from one dimensionalarray

3.            Implementation of  insertionsort.

4.            Implementation of  selectionsort.

5.            Implementation of BinarySearch.

6.            Implementation of Linear Search in a linkedlist

7.            Creation of a linked list and inserting nodes intoit.

8.            Deletion from a linkedlist.

9.            Implementation of  different operations on astack.

10.        Implementationofdifferentoperationsonaqueue

Text Books And Reference Books:

[1]   Silberschatz, P.B. Galvin and G. Gagne, Operating System  Concepts,  9th  Edition, New Delhi, Wiley India,2012.

Essential Reading / Recommended Reading

[1]    William Stallings, Operating system Internals and Design Principles, 7th Edition, Prentice Hall,2017.

[2]    Andrew S. Tanenbaum and Herbert Bos, Modern Operating Systems, 4th Edition, Pearson,2014.

[3]    H.M. Deitel, P. J. Deitel, D. R. Choffnes, Operating Systems, 3rd Edition, Pearson, 2007.

Evaluation Pattern

50% CIA + 50% Three Tests

ENG221 - ENGLISH - II (2020 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:2

Course Objectives/Course Description

 
  • To expose learners to a variety of texts to interact with
  • To help learners classify ideologies and be able to express the same
  • To expose learners to visual texts and its reading formulas
  • To help learners develop a taste to appreciate works of literature through the organization of language
  • To help develop critical thinking
  • To help learners appreciate literature and the language nuances that enhances its literary values
  • To help learners understand the relationship between the world around them and the text/literature
  • To help learners negotiate with content and infer meaning contextually
  • To help learners understand logical sequencing of content and process information

·         To help improve their communication skills for larger academic purposes and vocational purposes

·         To enable learners to learn the contextual use of words and the generic meaning

·         To enable learners to listen to audio content and infer contextual meaning

·         To enable learners to be able to speak for various purposes and occasions using context specific language and expressions

·         To enable learners to develop the ability to write for various purposes using suitable and precise language.

Learning Outcome

·         Understand how to engage with texts from various countries, historical, cultural specificities and politics

·         Understand and develop the ability to reflect upon and comment on texts with various themes

·         Develop an analytical and critical bent of mind to compare and analyze the various literature they read and discuss in class

·         Develop the ability to communicate both orally and in writing for various purposes

Unit-1
Teaching Hours:6
food
 

1.  Long text:    Witches’ Loaves

O Henry

2.   Short text:  Portion size is the trick!!!

By Ranjani Raman

Unit-1
Teaching Hours:6
language
 

Presentation skills

Unit-2
Teaching Hours:6
Fashion
 

1.Long text: In the Height of Fashion-Henry Lawson

 

2. short text: Crazy for Fashion- BabatundeAremu

Unit-2
Teaching Hours:6
Language
 

Report writing

Unit-3
Teaching Hours:6
Language
 

Group Discussion

Unit-3
Teaching Hours:6
Architecture
 

1.    long text:  Bharat Bhavan

By Charles Correa

2.   Short text:  The Plain Sense of Things

By Wallace Stevens

 

Unit-4
Teaching Hours:6
Management
 

1.Long Text: The Amazing Dabbawalas of Mumbai- ShivaniPandita

 

2. Short Text:

If

By Rudyard Kupling

Unit-4
Teaching Hours:6
Language
 

Interview skills and CV writing

Unit-5
Teaching Hours:6
History
 

1.    Long tet: Whose Ambedkar is he anyway?

           By KanchaIlaiah

 

2. Short text: Dhauli

By JayantaMahapatra

Unit-5
Teaching Hours:6
language
 

Developing arguments- debating

Unit-6
Teaching Hours:6
language
 

Letter writing and email writing

Unit-6
Teaching Hours:6
War
 

1.    Long text: An Occurrence at Owl Creek Bridge

By Ambrose Bierce

2.     Short text: Strange meeting

By Wilfred Owen

Unit-7
Teaching Hours:6
language
 

Ethics of writing on social media platforms

Unit-7
Teaching Hours:6
Social Media
 

1.Long text: Facebook and the Epiphanator: An

End to Endings?

            By Paul Ford

2. Short text:  'Truth in the time of Social Media' by Girish Balachandran

Unit-8
Teaching Hours:3
visual text
 

BBC Documentary- Dabbawalas

Text Books And Reference Books:

ENGlogue 1

Essential Reading / Recommended Reading

teacher manual and worksheets that teachers would provide. Listening skills worksheets.

Evaluation Pattern

CIA1- 20

MSE-50

CIA3- 20

ESE- 50 online and 50 written

FRN221 - FRENCH (2020 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

French as second language for the UG program

Learning Outcome

Enhancement of linguistic competencies and sharpening of written and oral communicative skills.

Unit-1
Teaching Hours:5
Chapter 4- Culture: A country of Vacations
 

Lesson 1: Hobbies

Unit-2
Teaching Hours:5
Chapter 4- Culture: A country of Vacations
 

Lesson 2: The routine

Unit-3
Teaching Hours:5
Poem
 

1. Demain dès l'aube - Victor Hugo

Unit-4
Teaching Hours:5
Chapter 5 - I discover
 

Lesson 1 : Where to shop?

Unit-5
Teaching Hours:5
Chapter 5: I discover
 

Lesson 2: Discover and Taste

Unit-6
Teaching Hours:5
Visual Text
 

A French Film

Unit-7
Teaching Hours:5
Chapter 6- Culture: Gourmet Countries
 

Lesson 1: Everyone is having fun

Unit-8
Teaching Hours:5
Poem
 

2. Le Lac - Alphonse de Lamartine

Unit-9
Teaching Hours:5
Chapter 6- Culture: Gourmet countries
 

Lesson 2: Daily routine of Teenagers

Text Books And Reference Books:

1.  Cocton, Marie-Noelle. Génération A1. Paris : Didier, 2016 

2.   Poèmes : Demain dès l'aube par Victor Hugo & Le Lac par Alphonse de Lamartine (contenu rédigé sur ligne)

Essential Reading / Recommended Reading

1.      Thakker, Viral. Plaisir d’écrire. New Delhi : Langers International Pvt. Ltd., 2011

2.      French websites like Bonjour de France, Fluent U French, Learn French Lab, Point du FLE etc.

Evaluation Pattern

Assessment Pattern

CIA (Weight)

ESE (Weight)

CIA 1 – Assignment & MOODLE Testing (Quiz)

10%

 

CIA 2 –Mid Sem Exam

25%

 

CIA 3 –DELF Pattern: Listening and Speaking /Role Play / Theatre

10%

 

Attendance

05%

 

End Sem Exam

 

50%

Total

50%

50%

MAT231 - DIFFERENTIAL EQUATIONS (2020 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 aims at introducing the students to the theory of ordinary and partial differential equations through various methods of solutions.

Course objectives​: This course will help the learner to

COBJ1. Solve first order ODE.

COBJ1. Solve higher order ODE with constant coefficients.

COBJ1. Solve second order linear differential equations with variable coefficients.

COBJ1. Form PDE and solve linear and non linear PDE’s of first order.

Learning Outcome

On successful completion of the course, the students should be able to

CO1. Understand the concepts of order, degree and linearity of ODE and recognize ODEs and PDEs.

CO2. Apply multiple approaches/appropriate techniques to solve first order ODEs.

CO3. Solve second order linear differential equations by finding Complementary function and particular integrals.

CO4. Solve second order linear differential equations with variable coefficients by different methods such as if part of the integral is known, exactness and method of variation of parameter.

CO5. Formulation of PDE by eliminating arbitrary constants and functions, solve linear PDEs using Lagrange’s auxiliary equation and solve nonlinear PDE’s of first order by Charpit’s method.

Unit-1
Teaching Hours:20
First Order ODE's
 

 

Solution of ordinary differential equations of first order and first degree – Variable separable and reducible to variable separable forms – Homogeneous and reducible to homogeneous forms – linear differential equations and reducible to linear differential equations – First order exact differential equations Integrating factors, rules to find an integrating factor – Clairauts equation – Orthogonal trajectory.

Unit-2
Teaching Hours:20
Explicit methods of solving higher order linear differential equations
 

Linear homogeneous equations with constant coefficients, Linear non-homogenous equations, The Cauchy-Euler equation, Simultaneous differential equations with constant coefficients. Second order linear differential equations with variable coefficients by the following methods: (i) when a part of complementary functions is given, (ii) reducing to normal form, (iii) change of independent variable (iv) variation of parameters and (v) by finding the first integral (exact equation), equations of the form (dx/P)=(dy/Q)=(dz/R).

Unit-3
Teaching Hours:20
Partial differential equations
 

Order and degree of partial differential equations, Formation of first order partial differential equations, Linear partial differential equation of first order, Lagrange’s method, Charpit’s method. Classification of second order partial differential equations into elliptic, parabolic and hyperbolic through illustrations only.

Text Books And Reference Books:
  1. G. F. Simmons, Differential Equations with Applications and Historical Notes, 2nd ed., New York McGraw Hill, 2006.
  2. I. Sneddon, Elements of Partial Differential Equations, McGraw-Hill, Reprint, Courier Corporation, 2013.
Essential Reading / Recommended Reading
  1. M. D. Raisinghania, Ordinary and Partial Differential Equation, Chand (S.) & Co. Ltd., India: March 17, 2005.
  2. D. G. Zill, W. S. Wright, Advanced Engineering Mathematics, 4th ed., Jones and Bartlett Publishers, 2010.
  3. S. L. Ross, Differential Equations, 3rd ed. (Reprint), John Wiley and Sons, 2007.
Evaluation Pattern
 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT251 - DIFFERENTIAL EQUATIONS USING MAXIMA (2020 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description:This course aims at introducing the students to an open source software MAXIMA and make students proficient in using Maxima for solving first and second order ODEs, study the nature of solution by plotting the general/particular solutions.

Course objectives​: This course will help the learner to

COBJ1. Acquire skill in solving problems on Differential Equations using MAXIMA.

COBJ2. Gain proficiency in using MAXIMA to solve problems on Differential Equations and its applications.

Learning Outcome

On successful completion of the course, the students should be able to

CO1. Acquire proficiency in using Maxima to study Differential Equations.

CO2. Demonstrate the use of Maxima to understand and interpret the core concepts in Differential Equations.

CO3. Find general and particular solutions of first and second order Differential Equations and to sketch the graph for solutions.

CO4. Apply MAXIMA to learn applications of Differential Equations in real world such as population, radioactive decay and Newton’s law of cooling.

Unit-1
Teaching Hours:30
Proposed Topics
 
  1. Construction of slope fields of an ordinary differential equation of the form.
  2. Sketch the slope fields for the given differential equations using wxMaxima.
  3. Sketch the slope fields for the given differential equations by highlighting three/four solution Curves.
  4. General solution of a first order differential equation and plotting families of curves representing them.
  5. To verify whether the given curves are solutions to the differential equations. Also sketch the graph of any 5 solution curves.
  6. To solve the initial value problems and sketch the solution curve.
  7. To solve a differential equation and sketch singular solution curve.
  8. Applications of First Order Differential Equations – a. Population Growth (Exponential/Logistic Model) and Radioactive decay (Four Case studies b.   Mixture Problems and Newton’s law of Cooling (Two case studies)
  9. Sketch Orthogonal Trajectories.
  10. General solution of a second order differential equation and plotting families of curves representing them.  
Text Books And Reference Books:
  1. Zachary Hannan, wxMaxima for Calculus I (Creative Commons Attribution Non-Commercial-Share Alike 4.0 International, Solano Community College, Edition 1.0 Publisher, Published June 17, 2015.
  2. Zachary Hannan, wxMaxima for Calculus II (Creative Commons Attribution-Non Commercial-Share Alike 4.0 International), Solano Community College, Edition 1.0      Publisher, Published June 17, 2015.
Essential Reading / Recommended Reading
  1. Sandeep Koranne, Handbook of Open Source Tools, Springer Science & Business Media, 2010.
  2. Velten, Mathematical Modeling and Simulation: Introduction for Scientists and Engineers, John Wiley and Sons, 2009.
Evaluation Pattern

The course is evaluated based on continuous internal assessments (CIA) and the lab e-record. The parameters for evaluation under each component and the mode of assessment are given below.

Component

Parameter

Mode of  Assessment

Maximum

Points

CIA I

Mastery of the  concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately,.

Lab Exam - II

10

Total

50

STA231 - STATISTICAL METHODS (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course is designed to teach the basic concepts of random variables and its generation functions. It also gives a brief idea about standard probability distributions and how they are applied in real time situations.

Learning Outcome

 

1.              :1.      Demonstrate the random variables and its functions

2.      Infer the expectations for random variable functions and generating functions.

3.      Demonstrate various discrete and continuous distributions and their usage

Unit-1
Teaching Hours:10
Random Variables
 

Definition, Discrete and continuous random variables, Probability Mass function and Probability density function, Distribution function and its properties. Two dimension random variables: Discrete and continuous type, Joint Density function, Marginal and conditional Probability Mass function and Probability Density function, independence of variables with illustration.

Unit-2
Teaching Hours:10
Mathematical Expectation and Generating functions
 

Expectation of single and bivariate random variables and its properties. Moments and Cumulants, moment generating function, cumulant generating function and characteristic function. Uniqueness and inversion theorems (without proof) along with applications, Conditional expectations.

Unit-3
Teaching Hours:15
Discrete Probability distributions
 

 

Discrete distributions: Binomial, Poisson, geometric, negative binomial, Hypergeometric distributions along with their properties, limiting/approximation cases and applications.

 

Unit-4
Teaching Hours:15
Continuous Probability distributions
 

Continuous distributions: Uniform, normal, exponential, Cauchy, beta and gamma distributions along with their properties, limiting/approximation cases and applications.

Unit-5
Teaching Hours:10
Limiting Theorems
 

Chebyshev’s inequality, Week Law of Large numbers, Strong Law of Large numbers and their applications, Central Limit Theorem for i.i.d variates and its application, De-Moivre Laplace theorem.

Text Books And Reference Books:

  1. 1.      Sheldon Ross, A First Course in Probability, 9th edition, Pearson Education, US, 2019.

    2.      Gupta S.C and Kapoor V.K, Fundamentals of Mathematical Statistics, Sultan Chand & Sons, New Delhi, 2014.

 

Essential Reading / Recommended Reading

  1. Mukhopadhyay P, Mathematical Statistics, Books and Allied (P) Ltd, Kolkata, 2015.
  2. Walpole R.E, Myers R.H, and Myers S.L, Probability and Statistics for Engineers and Scientists, Pearson, New Delhi, 2017.
  3. Montgomery D.C and Runger G.C, Applied Statistics and Probability for Engineers, Wiley India, New Delhi, 2013.
  4. Mood A.M, Graybill F.A and Boes D.C, Introduction to the Theory of Statistics, McGraw Hill, New Delhi, 2008.

 

Evaluation Pattern

 

Component

Marks

CIA I

10

Mid Semester Examination (CIA II)

25

CIA III

10

Attendance

05

End Semester Exam

50

Total

100

STA232 - R PROGRAMMING (2020 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course is used to provide an introduction to R, statistical language and environment that provides more flexible graph capabilities than other popular statistical packages. The course also covers the basics of R for statistical computation, exploratory analysis, and modeling

Learning Outcome

  CO1: Handle data using statistical tool

 CO2: Perform graphical representation of data using R

  CO3:  Use R for an introductory statistics

Unit-1
Teaching Hours:12
Introduction
 

Introduction and preliminaries-The R environment, R and statistics, R commands, Data permanency and removing objects,  Simple manipulations,  Numbers and Vectors,  Objects- modes and attributes, Ordered and unordered Factors, Arrays and Matrices

Unit-2
Teaching Hours:12
Lists and Data Frames
 

Constructing and modifying lists, Making Data frames, attach( ) and detach( ), Working with data frame, Reading data from files using read.table( ), scan( ), Grouping, Conditional execution: if statements, Repetitive execution: for loops, repeat and while loops, Functions.

Unit-3
Teaching Hours:12
Data Exploration for Univariate and Bivariate Data
 

Univariate Data - Handling categorical data and numerical data using R, Bivariate Data -Handling bivariate categorical data using R, Categorical vs. Numerical, Numerical vs. Numerical

Unit-4
Teaching Hours:12
Data Exploration for Multivariate Data
 

Multivariate Data -Storing multivariate data in R data frames, Accessing and manipulating data in R data frames, view multivariate data, apply( ) family functions - apply( ), sapply( ), lapply( ), tapply( ), dplyr package- select( ), filter( ), arrange( ), rename( ), mutate( ), group_by( ), %>%, summarize( ).

Unit-5
Teaching Hours:12
Correlation