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Bachelor of Technology in Computer Science- Block Chain Technology

Apply NowFind Programme

Bachelor of Technology in Computer Science- Block Chain Technology

School of Engineering and Technology (SET)

  • Programme Code

    SET0101

  • Level

    Graduate

  • Duration

    4 Years

Apply Now
About the Programme

Bachelor of Technology in Block Chain Technology is a four-year undergraduate programme that familiarises students with the functional and operational aspects of the cryptocurrency ecosystem. During the tenure of this programme, students develop an understanding of the emerging abstract models for Blockchain Technology.

The primary objective of this course is to identify significant research challenges and technical gaps existing between theory and practice in cryptocurrency domain and to quickly configure a new development platform to understand the applications of blockchain in cybersecurity, the integrity of information, E-Governance and other contract enforcement mechanisms.

The curriculum of this programme is designed in such a way that students are exposed to the Basic Cryptographic primitives used in Blockchain, Basic Distributed System concepts, Basic Blockchain concepts, Limitations of blockchain as a technology, and myths vs reality of blockchain technology and have an understanding and working knowledge of the emerging blockchain technology.

Programme Educational Objectives (PEO)

Program educational objectives are broad statements that describe the career and professional accomplishments that the program is preparing graduates to achieve.
The Program Educational Objectives (PEOs) of UG Program in Computer Science & Engineering are:

  • PEO-1 The graduates will establish themselves as professionals by solving real-life problems using exploratory and analytical skills acquired in the field of Computer Science and Engineering.
  • PEO-2 The graduates will provide sustainable solutions to ever changing interdisciplinary global problems through their Research & Innovation capabilities.
  • PEO-3 The graduates will become employable, successful entrepreneur as an outcome of Industry-Academia collaboration. 
  • PEO-4 The graduates will embrace professional code of ethics while providing solution to multidisciplinary social problems in industrial, entrepreneurial and research environment to demonstrate leadership qualities.

Methods of Forming PEO’s

  • STEP 1.    The needs of the Nation and society are identified through scientific publications, industry interaction and media.
  • STEP 2.    Taking the above into consideration, the PEOs are established by the Coordination Committee of the department.
  • STEP 3.   The PEOs are communicated to the alumni and their suggestions are obtained.
  • STEP 4.   The PEOs are communicated to all the faculty members of the department and their feedback is obtained.
  • STEP 5.   The PEOs are then put to the Board of Studies of the department for final approval.

Program Outcomes (PO’s)

  • PO1:  Engineering knowledge:  Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • PO2:  Problem analysis:  Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  • PO3:  Design/development of solutions:  Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  • PO4:  Conduct investigations of complex problems:  Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  • PO5:  Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
  • PO6:  The engineer and society:  Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  • PO7:  Environment and sustainability:  Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • PO8:  Ethics:  Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO9:  Individual and team work:  Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • PO10:  Communication:  Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  • PO11:  Project management and finance:  Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  • PO12:  Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

PSO's:

  • PSO1:  Experiment and prepare programming concepts and provide new ideas and innovations towards research and societal issues.
  • PSO2:  Analyse and develop computer programs in the areas related to algorithms, system software, cloud computing, artificial intelligence & machine learning, bioinformatics, big data analytics, block chain, cyber security and networking for efficient design of computer-based systems of varying complexity.
  • PSO3:  Apply standard Software Engineering practices and strategies in software project development using open-source programming environment to deliver a quality product for business success.

Programme Educational Objectives (PEO)

Program educational objectives are broad statements that describe the career and professional accomplishments that the program is preparing graduates to achieve.
The Program Educational Objectives (PEOs) of UG Program in Computer Science & Engineering are:

  • PEO-1 The graduates will establish themselves as professionals by solving real-life problems using exploratory and analytical skills acquired in the field of Computer Science and Engineering.
  • PEO-2 The graduates will provide sustainable solutions to ever changing interdisciplinary global problems through their Research & Innovation capabilities.
  • PEO-3 The graduates will become employable, successful entrepreneur as an outcome of Industry-Academia collaboration. 
  • PEO-4 The graduates will embrace professional code of ethics while providing solution to multidisciplinary social problems in industrial, entrepreneurial and research environment to demonstrate leadership qualities.

Methods of Forming PEO’s

  • STEP 1.    The needs of the Nation and society are identified through scientific publications, industry interaction and media.
  • STEP 2.  Taking the above into consideration, the PEOs are established by the Coordination Committee of the department.
  • STEP 3.   The PEOs are communicated to the alumni and their suggestions are obtained.
  • STEP 4.   The PEOs are communicated to all the faculty members of the department and their feedback is obtained.
  • STEP 5.   The PEOs are then put to the Board of Studies of the department for final approval.

Program Outcomes (PO’s)

  • PO1:Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • PO2:  Problem analysis:  Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  • PO3:  Design/development of solutions:  Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  • PO4:  Conduct investigations of complex problems:  Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  • PO5:  Modern tool usage:  Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
  • PO6:  The engineer and society:  Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  • PO7:    Environment and sustainability:  Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • PO8:  Ethics:  Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO9:  Individual and teamwork:  Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • PO10: Communication:  Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  • PO11: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  • PO12:Life-long learning:  Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
  • PSO1:  Experiment and prepare programming concepts and provide new ideas and innovations towards research and societal issues.
  • PSO2:  Analyse and develop computer programs in the areas related to algorithms, system software, cloud computing, artificial intelligence & machine learning, bioinformatics, big data analytics, block chain, cyber security and networking for efficient design of computer-based systems of varying complexity.
  • PSO3:  Apply standard Software Engineering practices and strategies in software project development using open-source programming environment to deliver a quality product for business success.

This course is for individuals who...

seek in-depth specialisation in the fields of blockchain technology, cryptocurrency and blockchain programming language. One can gain advanced and in-depth knowledge of Solidity programming language, distributed ledger cloud platform, Ethereum and Bitcoin cryptocurrency and can exploit research using a very hands-on approach.

Students who are looking for...

a career with exceptional prospective fields and challenging roles in a futuristic industry. The financial security, the freedom to relocate, lifelong prospects of learning makes this programme an ideal career for computer science enthusiasts.

Course Fee
For National Students
1st Year 184370 2nd Year 189901 3rd Year 195600 4th Year 201468
For International Students
Fee Per Semester Fee Per Year
2050 4000**
Programme Structure

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: I

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE113

Programming for Problem Solving

3

0

0

3

2

MTH142

Calculus and Abstract Algebra

3

1

0

4

3

PHY125

Engineering Physics-I

3

1

0

4

4

EVS103

Environmental Studies

2

0

0

2

OR

HMM111

Human Value & Ethics

Practical/Viva-Voce/Jury

5

ARP101

Communicative English-1

1

0

2

2

6

CSP113

Programming for Problem Solving Lab

0

0

2

1

7

CSP101

Introduction to Computer Science and Engineering

0

0

2

1

8

MEP106

Computer Aided Design & Drafting

0

0

3

1.5

OR

MEP105

Mechanical Workshop

0

0

3

9

PHY162

Physics Lab

0

0

2

1

TOTAL CREDITS

 

 

 

 

19.5

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: II

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE114

Application based Programming in Python

3

0

0

3

2

MTH145

Probability and Statistics                                                                                                                         

3

1

0

4

3

EEE112

Principles of Electrical and Electronics Engineering

2

1

0

3

4

HMM111

Human Value & Ethics

2

0

0

2

OR

EVS103

Environmental Studies

Practical/Viva-Voce/Jury

5

ARP102

Communicative English -2

1

0

2

2

6

CSP105

Design and creativity Lab

1

0

2

2

7

CSP114

Application based Programming in Python

0

0

2

1

8

MEP105

Mechanical Workshop

0

0

3

1.5

OR

MEP106

Computer Aided Design & Drafting

0

0

3

9

EEP112

Principles of Electrical and Electronics Engineering

0

0

2

1

TOTAL CREDITS

 

 

 

 

19.5

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: III

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE242

Data Structures

3

0

0

3

2

CSE245

Discrete Structures

3

1

0

4

3

CSE247

Computer Organization and Architecture

3

0

0

3

4

CSE253

Object Oriented Programming Using Java

2

0

0

2

5

CSE254

Principles of Operating System

2

0

0

2

6

CSE255

Introduction of Entrepreneurship

2

0

0

2

Practical/Viva-Voce/Jury

7

ARP203

Aptitude Reasoning and Business Communication Skills -  Basic

1

0

2

2

8

CSP242

Data Structures Lab

0

0

2

1

9

CSP243

Object Oriented Programming Using Java

0

0

2

1

10

CSP244

Principles of Operating System Lab

0

0

2

1

11

CSP254

Project Based Learning (PBL) -1

0

0

4

2

12

CSP292

Summer Internship-I

-

-

-

2

TOTAL CREDITS

 

 

 

 

25

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: IV

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

BTY223

Introduction to Biology for Engineers

2

0

0

2

2

CSE249

Data Base Management System

3

0

0

3

3

CSE251

Theory of Computation

3

1

0

4

4

CSE252

Computer Networks

3

0

0

3

5

PE-1

Program Elective-1

3

0

0

3

CSE011

Mathematical Techniques

CSE012

Introduction to Graph Theory and its Applications

6

OE1

Open Elective – 1

2

0

0

2

Practical/Viva-Voce/Jury

7

ARP204

Aptitude Reasoning and Business Communication Skills- Intermediate

1

0

2

2

8

CSP249

Data Base Management System Lab

0

0

2

1

9

CSP252

Computer Networks Lab

0

0

2

1

10

CSP297

Project Based Learning (PBL) -2

0

0

4

2

TOTAL CREDITS

 

 

 

 

23

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: V

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE354

Design and Analysis of Algorithm

3

0

0

3

2

CSE356

Software Engineering and Testing Methodologies

2

0

0

2

3

CSE355

Research Methodology

2

0

0

2

4

PE2

Program Elective-2

 

 

 

3

CSE021

Introduction to Cloud Computing

3

0

0

CSE023/ CSP023

Android Application Development

2

0

2

CSE024/ CSP024

Web Technologies

5

  OE-2

Open Elective – 2

2

0

0

2

Practical/Viva-Voce/Jury

6

ARP301

Quantitative Aptitude Behavioral and Interpersonal Skills

1

0

2

2

7

CSP350

Design and Analysis of Algorithm Lab

0

0

2

1

8

CSP354

Project Based Learning (PBL) -3

0

0

4

2

9

CSP355

Software Engineering and Testing Methodologies

0

0

2

1

10

CSP391

Summer Internship-II

-

-

-

2

11

CSP395

Technical Skill Enhancement Course-1 Simulation Lab

0

0

2

1

12

ECC301

Community Connect

-

-

-

2

TOTAL CREDITS

 

 

 

 

23

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: VI

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE353

Compiler Design

3

0

0

3

2

HMM305

Management for Engineers

3

0

0

3

3

PE3

Program Elective-3

3

0

0

3

CSE031

Digital Image Processing

CSE032

Cryptography and Network Security

4

PE4

Program Elective-4

3

0

0

3

CSE041

Software Project Management

CSE042

Software Testing

5

PE5

Program Elective-5

3

0

0

3

CSE051

Wireless Networks

CSE052

Risk Management

CSE053

Advanced Operating System

6

  OE-3

Open Elective – 3

3

0

0

3

Practical/Viva-Voce/Jury

7

ARP302

Higher Order Mathematics and Advanced People Skills

1

0

2

2

8

CSP353

Compiler Design Lab

0

0

2

1

9

CSP396

Technical Skill Enhancement Course-2(Application Development Lab)

0

0

2

1

10

CSP398

Project Based Learning (PBL) -4

0

0

4

2

TOTAL CREDITS

 

 

 

 

24

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: VII

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE472

Artificial Intelligence

3

0

0

3

2

 

Program Elective-6

3

0

0

3

CSE062

Mobile Computing

CSE063

Quantum Computing

3

 

Program Elective-7

2

0

0

2

CSE071

Introduction to Internet of Things

CSE072

Parallel Computing Algorithms

CSE073

3D Printing and Software Tools

4

 

Comprehensive Examination

0

0

0

0

5

OE4

Open Elective - 4

2

0

0

2

6

OE4

Open Elective - 5

3

0

0

3

Practical/Viva-Voce/Jury

7

CSP472

Artificial Intelligence Lab

0

0

2

1

8

CSP496

Summer Internship-III

-

-

-

2

9

CSP497

Capstone - 1

-

-

-

2

TOTAL CREDITS

 

 

 

 

18

School of Engineering and Technology

Department Of Computer Science & Engineering

B.Tech-Computer Science Engineering , Integrated B-Tech (CSE) + MBA, Integrated B-Tech (CSE) + M-Tech (SE)

Batch: 2021 Onwards

 

TERM: VIII

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

Practical/Viva-Voce/Jury

1

CSP498

Capstone  - 2

-

-

-

8

TOTAL CREDITS

 

 

 

 

8

S.No.

Course Code

Course Title

L

T

P

Credits

1

CSP101

Introduction to Artificial Intelligence and Machine Learning

0

0

2

1

2

CSE113/CSP113

Programming for Problem Solving

3

0

2

4

3

SC4

Maths I(Bucket based)

3

1

0

4

4

SC8

Engineering Physics

2

1

2

4

5

SC12

Computer Aided Design & Drafting

0

0

3

1.5

6

SC11

Principles of Electrical and Electronics Engineering

2

1

2

4

7

SC16

Soft Skill - 1

0

0

4

2

 

Credits in Term 1

 

 

 

20.5

Syllabus for  the Courses:

Introduction to Computer Science and Engineering: This course focuses application areas of Computer Science and Engineering for students admitted in undergraduate program. The purpose of B. Tech. in Computer Science & Engineering is to be given through this course to students.

Programming for problem solving: Programming for problem solving gives the Understanding of C programming and implement code from flowchart or algorithm

S.No.

Course Code

Course Title

L

T

P

Credits

1

CSE114/CSP114

Application based Programming in Python

3

0

2

4

2

SC5

Maths II(Bucket based)

3

1

0

4

3

SC9

Advanced Physics (Bucket based)

2

1

2

4

4

SC10

Engineering Chemistry

3

0

2

4

5

SC13

Mechanical Workshop

0

0

3

1.5

6

SC17

Soft Skill - 2

1

0

2

2

7

CSP103

(Design/creativity) Multimedia Application Lab

0

0

2

1

 

Credits in Term 2

 

 

 

20.5

Application Based Programming in Python : Python is a language with a simple syntax and a powerful set of libraries. It is widely used in many scientific areas for data exploration. This course is an introduction to the Python programming language for students without prior programming experience. We cover data types control flow object-oriented programming.

Multimedia and Animation Lab: This course is an overview of the modern technologies used for the Web development.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC18

CTS-1 Building Essential Language and life skills

0

0

4

2

2

SC14

Introduction to Biology for Engineers

2

0

0

2

3

MTH201

Discrete Structures

3

1

0

4

4

CSE247

Computer Organization and Architecture

3

0

0

3

5

CSE242/CSP242

Data Structures Using C

3

0

2

4

6

CSE243/CSP243

OOPS Using Java

3

0

2

4

7

PC3

Project Based Learning (PBL) -1

0

0

2

1

8

 

Industrial Internship

0

0

2

1

 

CSD201

Applied Stsistical Analysis

3

0

0

3

 

Credits in Term 3

 

 

 

24

Object Oriented Programming Using JAVA: Basic  Object Oriented Programming  (OOP) concepts including objects   classes methods parameter passing information hiding inheritance and polymorphism are introduced and their implementations using Java  are discussed.

Data Structures: This course  starts with an introduction to data structures with its classification efficiency of different algorithms array and pointer based implementations and Recursive applications. As the course progresses the study of Linear and Non-Linear data structures are studied in details. The course talks primarily about Linked list stacks queue Tree structure Graphs etc. This Course also deals with the concept of searching sorting and hashing methods.

Computer Organization and Architecture: This course discusses the basic structure of a digital computer and used for understanding the organization of various units such as control unit Arithmetic and Logical unit and Memory unit and I/O unit in a digital computer.

Applied Statistical Analysis: This graduate level course provides an introduction to the basic concepts of probability common distributions statistical methods and data analysis.

S.No.

Course Code

Course Title

L

T

P

Credits

1

CSP101

Introduction to Artificial Intelligence and Machine Learning

0

0

2

1

2

CSE113/CSP113

Programming for Problem Solving

3

0

2

4

3

SC4

Maths I(Bucket based)

3

1

0

4

4

SC8

Engineering Physics

2

1

2

4

5

SC12

Computer Aided Design & Drafting

0

0

3

1.5

6

SC11

Principles of Electrical and Electronics Engineering

2

1

2

4

7

SC16

Soft Skill - 1

0

0

4

2

 

Credits in Term 1

 

 

 

20.5

II. Syllabus for the Courses:

Introduction to Computer Science and Engineering: This course focuses application areas of Computer Science and Engineering for students admitted in undergraduate program. The purpose of B. Tech. in Computer Science & Engineering is to be given through this course to students.

Programming for problem solving: Programming for problem solving gives the Understanding of C programming and implement code from flowchart or algorithm

S.No.

Course Code

Course Title

L

T

P

Credits

1

CSE114/CSP114

Application based Programming in Python

3

0

2

4

2

SC5

Maths II(Bucket based)

3

1

0

4

3

SC9

Advanced Physics (Bucket based)

2

1

2

4

4

SC10

Engineering Chemistry

3

0

2

4

5

SC13

Mechanical Workshop

0

0

3

1.5

6

SC17

Soft Skill - 2

1

0

2

2

7

CSP103

(Design/creativity) Multimedia Application Lab

0

0

2

1

 

Credits in Term 2

 

 

 

20.5

Application Based Programming in Python : Python is a language with a simple syntax and a powerful set of libraries. It is widely used in many scientific areas for data exploration. This course is an introduction to the Python programming language for students without prior programming experience. We cover data types control flow object-oriented programming.

Multimedia and Animation Lab: This course is an overview of the modern technologies used for the Web development.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC18

CTS-1 Building Essential Language and life skills

0

0

4

2

2

SC14

Introduction to Biology for Engineers

2

0

0

2

3

MTH201

Discrete Structures

3

1

0

4

4

CSE247

Computer Organization and Architecture

3

0

0

3

5

CSE242/CSP242

Data Structures Using C

3

0

2

4

6

CSE243/CSP243

OOPS Using Java

3

0

2

4

7

PC3

Project Based Learning (PBL) -1

0

0

2

1

8

  PC4

Industrial Internship

0

0

2

1

 

CSA201

Soft computing

3

0

0

3

 

Credits in Term 3

 

 

 

24

Object Oriented Programming Using JAVA: Basic  Object Oriented Programming  (OOP) concepts including objects   classes methods parameter passing information hiding inheritance and polymorphism are introduced and their implementations using Java  are discussed.

Data Structures: This course  starts with an introduction to data structures with its classification efficiency of different algorithms array and pointer based implementations and Recursive applications. As the course progresses the study of Linear and Non-Linear data structures are studied in details. The course talks primarily about Linked list stacks queue Tree structure Graphs etc. This Course also deals with the concept of searching sorting and hashing methods.

Computer Organization and Architecture: This course discusses the basic structure of a digital computer and used for understanding the organization of various units such as control unit Arithmetic and Logical unit and Memory unit and I/O unit in a digital computer.

Soft Computing: This course introduces soft computing theories techniques and tools. Those are frequently required for understanding and developing the exploratory data analysis techniques and knowledge discovery and intelligent systems.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC19

CTS-2 Communicate to conquer

0

0

4

2

2

CSE244/CSp244

Principles of Operating System

3

0

2

4

3

CSE245/CSP245

Computer Networks

3

0

2

4

4

CSE246/CSP246

Data Base Management System

3

0

2

4

5

SC23

Management Course (from basket)

3

0

0

3

6

PC14

Project Based Learning (PBL) -2

0

0

2

1

7

SC7

Environmental Science

2

0

0

2

8

CSP201

Advance Java Lab

0

0

2

1

 

CSA202

Pattern Recognition

3

0

0

3

 

Credits in Term 4

 

 

 

24

Computer Network: To familiarize with the basic taxonomy and terminology of computer networking area.

Data Base Management systems: This course introduces database design and creation using a DBMS product. Emphasis is on normalization data integrity data modeling and creation of simple tables queries reports and forms. Upon completion students should be able to design and implement normalized database structures by creating simple database tables queries reports and forms.

Principles of Operating system: This course introduces the design principles of operating systems resource management identifying challenges and applying respective algorithms.     

  Advance Java Programming Lab: This course is designed to meet the needs of those who want to be professional Java developers. Students should be familiar with Java programming techniques and should be comfortable with concepts such as Classes Objects Inheritance Interfaces I/O Streams Threading and Networking.

Pattern Recognition: This course introduces neural computational paradigm for critical & implementable understanding of feature engineering.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC21

CTS-4 Ace the Interview

0

0

4

2

2

CSE344/CSP344

Compiler Design

3

0

2

4

3

CSE346/CSP346

Artificial Intelligence

3

0

2

4

4

CSP308

Technical Skill Enhancement Course-2(Statistical Analysis Lab)

0

0

2

1

5

PE2

Program Elective-2

3

0

0

3

6

PE3

Program Elective-3

3

0

0

3

7

PC16

Project Based Learning (PBL) -4

0

0

2

1

8

OE2

Open Elective - 2

3

0

0

3

 

CSA302

Neural Networks

3

0

0

3

 

Credits in Term 7

 

 

 

24

Compiler Design: To provide students with an overview of the issues that arise in Compiler construction as well as to throw light upon the significant theoretical developments and tools that are deep rooted into computer science.

Artificial Intelligence: This course introduces basic aspects of Artificial intelligence comparing the AI and conventional solutions to real world problems utilizing and analyze AI techniques for identifying optimal solutions to search strategies.

  Android Application Development: The course will introduce concepts of the Android platform Android application components Activities and their lifecycle UI design. It will also help students to build applications according to their problem statements.

  Introduction to Cloud Computing: This course introduces advanced aspects of Cloud Computing encompassing the principles to analyze the cloud identify the problems and choose the relevant models and algorithms to apply.

Software Project Management: This course introduces concepts of software project management in which Project Planning Project Evaluation Software Effort estimation Monitoring and control and Managing contracts tools and techniques are included.

Web Designing: This course is an overview of the modern Web technologies used for the Web development. The purpose of this course is to give students the basic understanding of how things work in the Web world from the technology point of view.

Natural Language Processing: This course introduces concepts of Basic  concepts of Natural Language and Grammar.

Information Retrieval: This course introduces neural computational paradigm for critical & implementable understanding for pattern based problem areas.

Neural Networks: This course introduces neural computational paradigm for critical & implementable understanding for pattern based problem areas.

S.No.

Course Code

Course Title

L

T

P

Credits

1

PE4

Program Elective-4

3

0

0

3

2

CSE458/CSP458

Web Technologies

3

0

2

4

3

SC26

Major Project- 1

0

0

6

3

4

SC22

Comprehensive Examination

0

0

0

0

5

SC28

Professional Ethics and Values

0

0

0

0

6

SC25

Industrial Internship

0

0

2

1

7

OE3

Open Elective - 3

2

0

0

2

8

 

CTS-5 Campus to corporate

0

0

2

1

 

CSA401

Introduction to Deep Leaning

3

0

0

3

 

Credits in Term 7

 

 

 

17

Web Technology:  The purpose of this course is to give students the basic understanding of how different computers and devices to communicate and share resources as well as to give the basic overview of the different technologies.

Digital Image Processing: This course is to study the image fundamentals and mathematical transforms necessary for image processing.

Wireless Network : Overview of wireless network architectures including cellular networks local area networks multi-hop wireless networks such as ad hoc networks mesh networks and sensor networks capacity of wireless networks medium access control routing protocols and transport protocols for wireless networks mechanisms to improve performance and security in wireless networks energy-efficient protocols for sensor networks.

  Mobile Computing: This course will give you an understanding of mobile computer systems particularly in the context of wireless network systems such as 2G/3G/4G mobile telephony data networks and other wireless networks and infrastructure.

Software Testing: This course will examine fundamental software testing and related program analysis techniques. The important phases of testing will be reviewed emphasizing the significance of each phase when testing different types of software. The course will also include concepts such as test generation test coverage regression testing mutation testing program analysis (e.g. program-flow and data-flow analysis) and test prioritization.

Digital Image Processing: This course will give you an understanding the image fundamentals and mathematical transforms necessary for image processing.

Introduction to Deep Leaning: This course introduces neural computational paradigm for critical & implementable understanding for automated learning based problem areas.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC27

Major Project - 2

0

0

18

9

2

PE6

Program Elective-5

3

0

0

3

3

PE5

Program Elective-6

3

0

0

3

4

OE4

Open Elective - 4

3

0

0

3

5

  SC

Universal Human Value & Ethics

2

0

0

2

 

CSA402

Robotics and Intelligent Systems

3

0

2

4

 

Credits in Term 8

 

 

 

20

PE-1

PE-2

PE-3

PE-4

PE-5

PE-6

                                                                                                                                                                  Introduction to Mathematical & Statistical Techniques in Computer Science                                                CSE348                             

Introduction to Cloud Computing  CSE351

Information Retrevial CSA304

Digital Image Processing CSA403

Fuzzy Logic CSA404

Intelligent Agents
CSA405

Introduction to Graph Theory and its Applications CSE349

Natural Language Processing CSA303

 

 

 

Introduction to Internet of Things CSI201

Program Elective List

 

Total Credits: __180___

Minimum Credits essential for the Programme:__180___

 

 

Distributed System Concepts & Design: This course covers issues and solutions related to the design and the implementation of distributed algorithms for different issues of distributed system.

  Introduction to Internet of Things: This course introduces Concepts for internet of things and how we can embed it into our daily lives for the development of life style. It will also help students to build applications according to their problem statements.

Fuzzy Logic: This course introduces Basic  concepts of Set Theory with functions and relational model.

Intelligent Agents:

Robotics and Intelligent Systems

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC20

CTS-3 Impress 2 Impact

0

0

4

2

2

CSE341/CSP341

Design and Analysis of Algorithm

3

0

2

4

3

CSE342

Theory of Computation

3

1

0

4

4

CSE343

Software Engineering and Testing Methodologies

3

0

0

3

5

PE1

Program Elective-1

3

0

0

3

6

CSP302

Technical Skill Enhancement Course-1(LINUX Programming Lab)

0

0

2

1

7

PC15

Project Based Learning (PBL) -3

0

0

2

1

8

OE1

Open Elective - 1

3

0

0

3

9

  PC5

Industrial Internship-II

0

0

2

1

 

CSA301

Introduction to Machine Learning

3

0

2

4

 

Credits in Term 5

 

 

 

26

Theory of computation: The course introduces some fundamental concepts in automata theory and formal languages including grammar finite automaton regular expression formal language pushdown automaton and Turing machine. Not only do they form basic models of computation they are also the foundation of many branches of computer science e.g. compilers software engineering concurrent systems etc. The properties of these models will be studied and various rigorous techniques for analyzing and comparing them will be discussed by using both formalism and examples.

Software Engineering and Testing Methodologies: The objective of this course is to provide fundamental knowledge of software engineering and make student aware of best software engineering practices and contemporary software engineering tools.

  Linux Programming Lab: The course is designed to make the students research/industry ready as by using the open source applications along with any of the Linux flavor operating systems.

Design and Analysis of Algorithms: This course introduces concepts related to the design and analysis of algorithms. Specifically it discusses recurrence relations and illustrates their role in asymptotic and probabilistic analysis of algorithms. It covers in detail greedy strategies divide and conquer techniques dynamic programming and max flow - min cut theory for designing algorithms and illustrates them using a number of well-known problems and applications.

Introduction to Graph Theory and its Application: This course is to teach students the basic graph theory concepts and their applications in computer science.

    Mathematical and Statistical Techniques: In this subject the fundamental concepts and principles of Mathematical & Statistical Techniques together with the challenging issues in Computer Science software development will be introduced.  Discussion on various topics related to mathematics and Computer Science will also be conducted.  

Introduction to Machine Learning: This course introduces computational learning paradigm for critical & implementable understanding for supervised and unsupervised learning based problem areas.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC19

CTS-2 Communicate to conquer

0

0

4

2

2

CSE244/CSp244

Principles of Operating System

3

0

2

4

3

CSE245/CSP245

Computer Networks

3

0

2

4

4

CSE246/CSP246

Data Base Management System

3

0

2

4

5

SC23

Management Course (from basket)

3

0

0

3

6

PC14

Project Based Learning (PBL) -2

0

0

2

1

7

SC7

Environmental Science

2

0

0

2

8

CSP201

Advance Java Lab

0

0

2

1

 

CSD202

Data Acquisition

3

0

0

3

 

Credits in Term 4

 

 

 

24

Computer Network: To familiarize with the basic taxonomy and terminology of computer networking area.

Data Base Management systems: This course introduces database design and creation using a DBMS product. Emphasis is on normalization data integrity data modeling and creation of simple tables queries reports and forms. Upon completion students should be able to design and implement normalized database structures by creating simple database tables queries reports and forms.

Principles of Operating system: This course introduces the design principles of operating systems resource management identifying challenges and applying respective algorithms.     

  Advance Java Programming Lab: This course is designed to meet the needs of those who want to be professional Java developers. Students should be familiar with Java programming techniques and should be comfortable with concepts such as Classes Objects Inheritance Interfaces I/O Streams Threading and Networking.

Data Acquisition: Major topics covered in this subjects are data acquision processs managing data Graphical representation of data Data Aggregation Group Operations Time series Visualization of data   Data Productization IoT   and Virtualization on Embedded Boards IoT.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC20

CTS-3 Impress 2 Impact

0

0

4

2

2

CSE341/CSP341

Design and Analysis of Algorithm

3

0

2

4

3

CSE342

Theory of Computation

3

1

0

4

4

CSE343

Software Engineering and Testing Methodologies

3

0

0

3

5

PE1

Program Elective-1

3

0

0

3

6

CSP302

Technical Skill Enhancement Course-1(LINUX Programming Lab)

0

0

2

1

7

PC15

Project Based Learning (PBL) -3

0

0

2

1

8

OE1

Open Elective - 1

3

0

0

3

9

 

Industrial Internship-II

0

0

2

1

10

CSD301

  Data Warehouse

3

0

0

3

 

Credits in Term 5

 

 

 

25

Theory of computation: The course introduces some fundamental concepts in automata theory and formal languages including grammar finite automaton regular expression formal language pushdown automaton and Turing machine. Not only do they form basic models of computation they are also the foundation of many branches of computer science e.g. compilers software engineering concurrent systems etc. The properties of these models will be studied and various rigorous techniques for analyzing and comparing them will be discussed by using both formalism and examples.

Software Engineering and Testing Methodologies: The objective of this course is to provide fundamental knowledge of software engineering and make student aware of best software engineering practices and contemporary software engineering tools.

  Linux Programming Lab: The course is designed to make the students research/industry ready as by using the open source applications along with any of the Linux flavor operating systems.

Design and Analysis of Algorithms: This course introduces concepts related to the design and analysis of algorithms. Specifically it discusses recurrence relations and illustrates their role in asymptotic and probabilistic analysis of algorithms. It covers in detail greedy strategies divide and conquer techniques dynamic programming and max flow - min cut theory for designing algorithms and illustrates them using a number of well-known problems and applications.

Introduction to Graph Theory and its Application: This course is to teach students the basic graph theory concepts and their applications in computer science.

Introduction Mathematical and Statistical Techniques: In this subject the fundamental concepts and principles of Mathematical & Statistical Techniques together with the challenging issues in Computer Science software development will be introduced.  Discussion on various topics related to mathematics and Computer Science will also be conducted. 

Data Warehouse: This course introduces advanced aspects of data warehousing encompassing the principles to analyze the data identify the problems and choose the relevant models and algorithms to apply.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC21

CTS-4 Ace the Interview

0

0

4

2

2

CSE344/CSP344

Compiler Design

3

0

2

4

3

CSE346/CSP346

Artificial Intelligence

3

0

2

4

4

CSP308

Technical Skill Enhancement Course-2(Statistical Analysis Lab)

0

0

2

1

5

PE2

Program Elective-2

3

0

0

3

6

PE3

Program Elective-3

3

0

0

3

7

PC16

Project Based Learning (PBL) -4

0

0

2

1

8

OE2

Open Elective - 2

3

0

0

3

 

CSD302

  Data Mining

3

0

2

4

 

Credits in Term 7

 

 

 

25

Compiler Design: To provide students with an overview of the issues that arise in Compiler construction as well as to throw light upon the significant theoretical developments and tools that are deep rooted into computer science.

Artificial Intelligence: This course introduces basic aspects of Artificial intelligence comparing the AI and conventional solutions to real world problems utilizing and analyze AI techniques for identifying optimal solutions to search strategies.

  Introduction to Cloud Computing: This course introduces advanced aspects of Cloud Computing encompassing the principles to analyze the cloud identify the problems and choose the relevant models and algorithms to apply.

Business Process Management (BPM) : Business Process Management (BPM) is a management discipline concerned with lifting an organization s performance through improvement management and control of business processes. It encapsulates methods techniques and software involved throughout all stages of the process lifecycle including analysis design enactment and control.

Social Media Analytics

Social Media Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us understand our world better and in many contexts enable us to make better decisions. 

Data Mining:   This course introduces advanced aspects of data warehousing and data mining encompassing the principles to analyze the data identify the problems and choose the relevant models and algorithms to apply.

S.No.

Course Code

Course Title

L

T

P

Credits

1

PE4

Program Elective-4

3

0

0

3

2

CSE458/CSP458

Web Technologies

3

0

2

4

3

SC26

Major Project- 1

0

0

6

3

4

SC22

Comprehensive Examination

0

0

0

0

5

SC28

Professional Ethics and Values

0

0

0

0

6

SC25

Industrial Internship

0

0

2

1

7

OE3

Open Elective - 3

2

0

0

2

8

 

CTS-5 Campus to corporate

0

0

2

1

9

CSD401

Business Intelligence

3

0

0

3

 

Credits in Term 7

 

 

 

17

Web Technology:   The purpose of this course is to give students the basic understanding of how different computers and devices to communicate and share resources as well as to give the basic overview of the different technologies.

Introduction to Deep Learning: This course introduces neural computational paradigm for critical & implementable understanding for automated learning based problem areas.

Business Intelligence: This course Have an overall understanding of the major issues and applications in business intelligence including a basic grasp of the algorithm classes and best practices for building successful BI projects.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC27

Major Project - 2

0

0

18

9

2

PE6

Program Elective-5

3

0

0

3

3

PE5

Program Elective-6

3

0

0

3

4

OE4

Open Elective - 4

3

0

0

3

5

 

Universal Human Value & Ethics

2

0

0

2

 

CSD402

Big Data Analytics

3

0

2

4

 

Credits in Term 8

 

 

 

24

Program Elective List:

PE-1

PE-2

PE-3

PE-4

PE-5

PE-6

                                                                                                                                                                  Introduction to Mathematical & Statistical Techniques in Computer Science                                                CSE348                             

Introduction to Cloud Computing  CSE351

Scocial Media Analytics CSD304

Introduction to Deep Learning CSA407

Web and Text    CSD403

Introduction to Internet of Things CSI201

Introduction to Graph Theory and its Applications CSE349

Business Process Management CSD303

 

 

 

Cluster Computing CSD404

Total Credits: __180___

Minimum Credits essential for the Programme:__180___

S.No.

Course Code

Course Title

L

T

P

Credits

1

CSP101

Introduction to Artificial Intelligence and Machine Learning

0

0

2

1

2

CSE113/CSP113

Programming for Problem Solving

3

0

2

4

3

SC4

Maths I(Bucket based)

3

1

0

4

4

SC8

Engineering Physics

2

1

2

4

5

SC12

Computer Aided Design & Drafting

0

0

3

1.5

6

SC11

Principles of Electrical and Electronics Engineering

2

1

2

4

7

SC16

Soft Skill – 1

0

0

4

2

 

Credits in Term 1

 

 

 

20.5

Introduction to Computer Science and Engineering: This course focuses application areas of Computer Science and Engineering for students admitted in undergraduate program. The purpose of B. Tech. in Computer Science & Engineering is to be given through this course to students.

Programming for problem solving: Programming for problem solving gives the Understanding of C programming and implement code from flowchart or algorithm

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC3

Application based Programming in Python

3

0

2

4

2

SC5

Maths II(Bucket based)

3

1

0

4

3

SC9

Advanced Physics (Bucket based)

2

1

2

4

4

SC10

Engineering Chemistry

3

0

2

4

5

SC13

Mechanical Workshop

0

0

3

1.5

6

SC17

Soft Skill – 2

1

0

2

2

7

SC24

(Design/creativity) Multimedia Application Lab

0

0

2

1

 

Credits in Term 2

 

 

 

20.5

Application Based Programming in Python : Python is a language with a simple syntax and a powerful set of libraries. It is widely used in many scientific areas for data exploration. This course is an introduction to the Python programming language for students without prior programming experience. We cover data types control flow object-oriented programming.

Multimedia and Animation Lab: This course is an overview of the modern technologies used for the Web development.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC18

CTS-1 Building Essential Language and life skills

0

0

4

2

2

SC14

Introduction to Biology for Engineers

2

0

0

2

3

MTH201

Discrete Structures

3

1

0

4

4

CSE247

Computer Organization and Architecture

3

0

0

3

5

CSE242/CSP242

Data Structures Using C

3

0

2

4

6

CSE243/CSP243

OOPS Using Java

3

0

2

4

7

PC3

Project Based Learning (PBL) -1

0

0

2

1

8

 

Industrial Internship

0

0

2

1

 

CSI201

Introduction to Internet  of Things

3

0

0

3

 

Credits in Term 3

 

 

 

24

Object Oriented Programming Using JAVA: Basic  Object Oriented Programming  (OOP) concepts including objects   classes methods parameter passing information hiding inheritance and polymorphism are introduced and their implementations using Java  are discussed.

Data Structures: This course  starts with an introduction to data structures with its classification efficiency of different algorithms array and pointer based implementations and Recursive applications. As the course progresses the study of Linear and Non-Linear data structures are studied in details. The course talks primarily about Linked list stacks queue Tree structure Graphs etc. This Course also deals with the concept of searching sorting and hashing methods.

Computer Organization and Architecture: This course discusses the basic structure of a digital computer and used for understanding the organization of various units such as control unit Arithmetic and Logical unit and Memory unit and I/O unit in a digital computer.

Introduction to Internet of Things: This course introduces Concepts for internet of things and how we can embed it into our daily lives for the development of life style. It will also help students to build applications according to their problem statements.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC19

CTS-2 Communicate to conquer

0

0

4

2

2

CSE244/CSp244

Principles of Operating System

3

0

2

4

3

CSE245/CSP245

Computer Networks

3

0

2

4

4

CSE246/CSP246

Data Base Management System

3

0

2

4

5

SC23

Management Course (from basket)

3

0

0

3

6

PC14

Project Based Learning (PBL) -2

0

0

2

1

7

SC7

Environmental Science

2

0

0

2

8

CSP201

Advance Java Lab

0

0

2

1

 

CSI202

IOT and Smart Sensors

3

0

2

4

 

Credits in Term 4

 

 

 

25

Computer Network: To familiarize with the basic taxonomy and terminology of computer networking area.

Data Base Management systems: This course introduces database design and creation using a DBMS product. Emphasis is on normalization data integrity data modeling and creation of simple tables queries reports and forms. Upon completion students should be able to design and implement normalized database structures by creating simple database tables queries reports and forms.

Principles of Operating system: This course introduces the design principles of operating systems resource management identifying challenges and applying respective algorithms.     

  Advance Java Programming Lab: This course is designed to meet the needs of those who want to be professional Java developers. Students should be familiar with Java programming techniques and should be comfortable with concepts such as Classes Objects Inheritance Interfaces I/O Streams Threading and Networking.

  Smart Sensors and Sensor Networking : This subject explores the latest sensor and sensor networks techniques and applications showing how networked wireless sensors are used to monitor and gather intelligence from our surrounding environment.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC20

CTS-3 Impress 2 Impact

0

0

4

2

2

CSE341/CSP341

Design and Analysis of Algorithm

3

0

2

4

3

CSE342

Theory of Computation

3

1

0

4

4

CSE343

Software Engineering and Testing Methodologies

3

0

0

3

5

PE1

Program Elective-1

3

0

0

3

6

CSP302

Technical Skill Enhancement Course-1(LINUX Programming Lab)

0

0

2

1

7

PC15

Project Based Learning (PBL) -3

0

0

2

1

8

OE1

Open Elective - 1

3

0

0

3

9

 

Industrial Internship-II

0

0

2

1

 

CSI301

Wireless sensor Networks

3

0

0

3

 

Credits in Term 5

 

 

 

25

Theory of computation: The course introduces some fundamental concepts in automata theory and formal languages including grammar finite automaton regular expression formal language pushdown automaton and Turing machine. Not only do they form basic models of computation they are also the foundation of many branches of computer science e.g. compilers software engineering concurrent systems etc. The properties of these models will be studied and various rigorous techniques for analyzing and comparing them will be discussed by using both formalism and examples.

Software Engineering and Testing Methodologies: The objective of this course is to provide fundamental knowledge of software engineering and make student aware of best software engineering practices and contemporary software engineering tools.

  Linux Programming Lab: The course is designed to make the students research/industry ready as by using the open source applications along with any of the Linux flavor operating systems.

Design and Analysis of Algorithms: This course introduces concepts related to the design and analysis of algorithms. Specifically it discusses recurrence relations and illustrates their role in asymptotic and probabilistic analysis of algorithms. It covers in detail greedy strategies divide and conquer techniques dynamic programming and max flow - min cut theory for designing algorithms and illustrates them using a number of well-known problems and applications.

Introduction to Graph Theory and its Application: This course is to teach students the basic graph theory concepts and their applications in computer science.

Mathematical and Statistical Techniques: In this subject the fundamental concepts and principles of Mathematical & Statistical Techniques together with the challenging issues in Computer Science software development will be introduced.  Discussion on various topics related to mathematics and Computer Science will also be conducted. 

Wireless sensor Networks: This subject gives the concept of spatially distributed autonomous devices using sensors to monitor physical or environmental conditions.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC21

CTS-4 Ace the Interview

0

0

4

2

2

CSE344/CSP344

Compiler Design

3

0

2

4

3

CSE346/CSP346

Artificial Intelligence

3

0

2

4

4

CSP308

Technical Skill Enhancement Course-2(Statistical Analysis Lab)

0

0

2

1

5

PE2

Program Elective-2

3

0

0

3

6

PE3

Program Elective-3

3

0

0

3

7

PC16

Project Based Learning (PBL) -4

0

0

2

1

8

OE2

Open Elective - 2

3

0

0

3

 

CSI302

Embedded systems

3

0

0

3

 

Credits in Term 7

 

 

 

24

Compiler Design: To provide students with an overview of the issues that arise in Compiler construction as well as to throw light upon the significant theoretical developments and tools that are deep rooted into computer science.

Artificial Intelligence: This course introduces basic aspects of Artificial intelligence comparing the AI and conventional solutions to real world problems utilizing and analyze AI techniques for identifying optimal solutions to search strategies.

  Introduction to Cloud Computing: This course introduces advanced aspects of Cloud Computing encompassing the principles to analyze the cloud identify the problems and choose the relevant models and algorithms to apply.

Big data analytics of IOT in IOT : This course provides a way to understand the concepts and the basics of big data analytics and their role in Internet of things.

Embedded systems: the fundamentals of embedded system hardware and firmware design will be explored. Issues such as embedded processor selection hardware/firmware partitioning glue logic circuit design circuit layout circuit debugging development tools firmware architecture firmware design and firmware debugging will be discussed. The Intel 8051 a very popular microcontroller will be studied. The architecture and instruction set of the microcontroller will be discussed.

S.No.

Course Code

Course Title

L

T

P

Credits

1

PE4

Program Elective-4

3

0

0

3

2

CSE458/CSP458

Web Technologies

3

0

2

4

3

SC26

Major Project- 1

0

0

6

3

4

SC22

Comprehensive Examination

0

0

0

0

5

SC28

Professional Ethics and Values

0

0

0

0

6

SC25

Industrial Internship

0

0

2

1

7

OE3

Open Elective - 3

2

0

0

2

8

 

CTS-5 Campus to corporate

0

0

2

1

 

CSI401

IOT Architecture and Protocols

3

0

0

3

 

Credits in Term 7

 

 

 

17

Web Technology:   The purpose of this course is to give students the basic understanding of how different computers and devices to communicate and share resources as well as to give the basic overview of the different technologies.

Introduction to Deep Learning: This course introduces neural computational paradigm for critical & implementable understanding for automated learning based problem areas.

IOT Architecture and Protocols: The purpose of this course is to impart knowledge on IoT Architecture and various protocols study their implementations.

Internet of things sensing and actuator devices: The purpose of this course is to impart knowledge on Internet of Things (IoT) which relates to the study of sensors actuators and controllers among other Things IoT applications and examples overview (building automation transportation healthcare industry etc.) with a focus on wearable electronics.

S.No.

Course Code

Course Title

L

T

P

Credits

1

SC27

Major Project - 2

0

0

18

9

2

PE6

Program Elective-5

3

0

0

3

3

PE5

Program Elective-6

3

0

0

3

4

OE4

Open Elective - 4

3

0

0

3

5

 

Universal Human Value & Ethics

2

0

0

2

 

CSI402

IOT Using RFID and microcontroller

3

0

2

4

 

Credits in Term 8

 

 

 

24

Program Elective List:

PE-1

PE-2

PE-3

PE-4

PE-5

PE-6

                                                                                                                                                                  Introduction to Mathematical & Statistical Techniques in Computer Science                                                CSE348                             

Introduction to Cloud Computing  CSE351

Data Sciences in IOT                                CSI304

Internet of things sensing and actuatur devices CSI403

IOT security CSI405

Industrial IOT CSI406

Introduction to Graph Theory and its Applications CSE349

Dynamic Paridgms in IOT CSI303

 

Introduction to Deep Learning CSA401

 

 

 

 

 

 

 

 

 

Total Credits: __180___

Minimum Credits essential for the Programme:__180___

IOT security: Objective of this course is to understand the Security requirements in IoT to understand the cryptographic fundamentals for IoT

Also this course will help student understand the various types Trust models and Cloud Security.

Industrial Network Protocols and IoT:

IOT Using RFID and microcontroller:

Eligibility Criteria
For National Students
  • Matriculation with-60% marks Sr. Secondary (10+2) 70% marks (Aggregate) & minimum 60% marks in PCM
  • Computer Science/PCB for Biotechnology without gap between 10th and 12th. Minimum 50% marks in Maths

+

  • SUAT (Online Test) Followed by Personal Interview

or

  • JEE All India Rank upto 3 Lakh

or

  • UPSEE All India Rank upto 50 000
For International Students The eligibility criterion for all programs for international applicants is minimum 50% in the qualifying examination and having studied the pre-requisite subjects for admission in to the desired program.
Career path you can choose after the course
  • Blockchain Developer
  • Bitcoin cryptocurrency developer
  • Blockchain Software Engineer
  • Blockchain Principal Program Manager
  • Blockchain SI Partner Development Manager
  • Business Analytics Associate
  • IBM
  • Microsoft
  • Accenture
  • Visa

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