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M.Tech. CSE- Data Science

M.Tech. CSE- Data Science

School of Engineering and Technology (SET)

  • Programme Code

    SET0130

  • Level

    Post Graduate

  • Duration

    2 Years

About the Programme

M. Tech CSE Data Science is a two-year post-graduate programme with an objective to impart knowledge on techniques and theories related to data science which includes statistics, data mining, data warehousing and data visualisation. The programme enables students to apply the knowledge of computing techniques and tools in the field of Big Data for solving real world problems encountered in various industries.
This programme is useful for students who wish to develop and utilise their skills to achieve a thorough knowledge of data science and engineering. Some of these are the ability to aggregate interpret and manage a large amount of heterogeneous data resources independent of the hardware and software resources. The programme consists of the modules to be learnt as compulsory electives along with core subjects of computer science and engineering. Few of them include:

  • Data Acquisition and Production
  • Machine Learning.
  • Mathematical and statistical Techniques in Computer science
  • Soft Computing Techniques
  • Analysis and Design of algorithm.
  • Image and Video Analysis
  • Massive and Graphic Analysis
  • Machine Learning
  • Advanced Web Analytics
  • Deep Learning and Web
  • Bioinformatics
  • Health Care and Analytics

Programme Educational Objectives (PEO)

  • 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.

Program Outcomes (PO’s)

  • PO1: Advanced Technical Knowledge Ability to apply advanced knowledge of mathematical, scientific and computing to carry out independent research and investigate complex problems of global benchmark.
  • PO2: Research and Development Achieve and understand research-based solutions for problems in industry and academia using contemporary research methods.
  • PO3: Pedagogy Enables academic adherence by practice of method and environment for teaching which is incorporated within the curriculum enabling life-long learning and professional development through self-study, continuing education, professional and doctoral level studies.
  • PO4: Innovation and Entrepreneurial Inculcate innovative approaches to develop solutions towards existing real-world problem(s) to create value and wealth for the betterment of the individual and society at large.
  •   PO5: Societal Values Inculcating the human, social and business context while knowledge discovery by providing exposure to global view and diversity in the world and will utilize their engineering skills.
  • PO6: Personal and Professional Ethics Recognize the need of ethical, legal and societal implications to engage in self-governing and lifelong learning by making use of professional principles.
  • PO7: Communication Skills Ability to develop communication skills so that they are able to express ideas clearly and persuasively, in written and oral forms in a substantial technical manner.
  • PO8: Life-long learning Ability to engage in independent and life-long learning in the broadest context of research and technological change with the aim to educate the society and peers.

PSO’s

  • PSO1: Software Engineering To apply the software engineering principles and practices to provide high quality software solutions using state of art technologies.
  • PSO2: Data Science & Analytics To develop research solutions in the field of data engineering by using modern tools to provide innovative solutions for complex data science problems.
  • PSO3: Networking and Cyber Security To apply networking principles to understand cyber security issues and provides solutions to real world security problems

This course is for individuals who...

are interested in developing computational and statistical skills for data-driven multi-disciplinary problems.

Students who are looking for...

a career in areas such as machine learning, deep learning, data mining, predictive analysis, large scale data analytics and big data.

Course Fee
For National Students
1st Year 100786 2nd Year 103809
For International Students
Fee Per Semester Fee Per Year
2550 5000**
Programme Structure

School of Engineering and Technology

Department Of Computer Science & Engineering

M.Tech CSE with specialization in Software Engineering

Batch: 2019 Onwards

 

TERM: I (Spring-II)

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE611

Analysis and Design of Algorithms

3

1

0

4

2

CSE613

Mathematical and Statistical Techniques in Computer Science

3

1

0

4

3

 

Departmental Elective-1

3

0

0

3

CSE640

Object Oriented Software Engineering

CSE651

Software Architecture and Design Pattern.

4

 

Departmental Elective-2

 

 

 

 

CSE642

Soft Computing Techniques

3

0

0

3

5

 

Departmental Elective-3

3

0

0

3

CSE643

Software Requirement and Estimation

CSE652

Software Quality Metrics and Testing

Practical/Viva-Voce/Jury

1

CSP611

Analysis and Design of Algorithms Lab

0

0

2

1

2

 

Departmental Elective-1

0

0

2

1

CSP640

Object Oriented Software Engineering Lab

CSP651

Software Architecture and Design Pattern Lab

TOTAL CREDITS

19

School of Engineering and Technology

Department Of Computer Science & Engineering

M.Tech CSE with specialization in Software Engineering

Batch: 2019 Onwards

 

TERM: II (Spring-I)

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

THEORY SUBJECTS

1

CSE650

Pattern Recognition

3

1

0

4

2

CSE605

Machine Learning

3

0

0

3

3

 

Departmental Elective-4

3

0

0

3

CSE644

Agile Based Software Engineering

  CSE649

Secure Software Engineering

4

 

Departmental Elective-5

2

0

0

2

  CSE648

Recent Advances in Software Engineering.

5

 

Departmental Elective-6

3

0

0

3

CSE635

Software Reliability Engineering

 

Web Engineering

6

 

Departmental Elective-7

3

0

0

3

CSE647 

Component Based Software Engineering 

7

MRM001

Research Methodology

2

0

0

2

Practical/Viva-Voce/Jury

1

CSP650

Pattern Recognition Lab

0

0

2

1

2

 

Departmental Elective-4

0

0

2

1

CSP644

Agile Based Software Engineering Lab

  CSP649

Secure Software Engineering Lab

3

 

Departmental Elective-5

0

0

2

1

  CSP648

Recent Advances in Software Engineering Lab

4

CCU101

Community Connect

-

-

-

2

TOTAL CREDITS

25

School of Engineering and Technology

Department Of Computer Science & Engineering

Master of Technology- Computer Science and Engineering

Batch: 2019 Onwards

 

TERM: III

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

Practical/Viva-Voce/Jury

1

CSP681

Seminar

-

-

-

2

2

CSP691

Dissertation 1

-

-

-

10

TOTAL CREDITS

 

 

 

 

12

School of Engineering and Technology

Department Of Computer Science & Engineering

Master of Technology- Computer Science and Engineering

Batch: 2019 Onwards

 

TERM: IV

S. No.

Course Code

Course

Teaching Load

Credits

L

T

P

Practical/Viva-Voce/Jury

1.           

CSP692

Dissertation-II

-

-

-

                                                                                                          16

TOTAL CREDITS

 

 

 

 

16

Eligibility Criteria
For National Students
  • B.Tech. in Computer Science IT Electronics & Communication Electronics & Instrumentation and Electrical & Electronics with minimum 60% marks. MCA/M.Sc. (Computer Sc.) with minimum 60% marks.
  • GATE/NET Qualified students shall be preferred.
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
  • Data Scientist
  • Data Analytic
  • R& D
  • Banks
  • IT Consultancies
  • Research
  • Academician in Colleges/Universities

Students of this programme are placed in companies with an average annual package of 4.50 LPA to 12.00 LPA

Take the next step towards a career in engineering.

Apply Now