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M.Sc. Data Science & Analytics

M.Sc. Data Science & Analytics

School of Basic Sciences & Research (SBSR)

  • Programme Code

    SBSR0309

  • Level

    Post Graduate

  • Duration

    2 Years

About the Programme

Data science is poised to reshape our global economy, reinventing how we conduct business, and improving our lives in a variety of ways. Data scientists are in high demand across industries, with their ability to assist businesses in making data-driven decisions being highly valued.

You've come to the correct place if you're interested in extracting knowledge and insights from large data sets and want to put your skills to use in a meaningful profession. The Sharda University curriculum will assist you in learning the skills required for a successful data science profession.

To mention a few, you'll learn essential competencies in Machine Learning, Data Mining, and Predictive Analytics.

  Programme Educational Objectives (PEO’s)

  • PEO1: The graduates will achieve deep subject knowledge in the courses of study to enable employed in industry, government and entrepreneurial endeavors to have a successful professional career.
  • PEO2: The graduates will develop positive attitude and skills to enable a multi facet personality.
  • PEO3: The graduates will prepare for pursue higher education and research.
  • PEO4: The graduates will develop for contribute to the society and human well-being by applying ethical principles.

Program Outcomes (PO’s)

  • PO1: Data Science knowledge: Engage in continuous reflective learning in the context of technology and scientific advancement.
  • PO2: Modern software tool usage: Acquire the skills in handling data science programming tools towards problem solving and solution analysis for domain specific problems.
  • PO3: Critical thinking: Ability to understand the abstract concepts that lead to various data science theories in Mathematics, Statistics and Computer science.
  • PO4: Problem analysis: Problem analysis and design ability to identify analyze and design solutions for data science problems using fundamental principles of mathematics, Statistics, computing sciences, and relevant domain disciplines.
  • PO5: Innovation and Entrepreneurship:Produce innovative IT solutions and services based on global needs and trends.

Programme Specific Outcomes (PSO’s)

  • PSO1: Utilize the data science theories for societal and environmental concerns.
  • PSO2: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices.
  • PSO3: 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.
  • PSO4: Understand the role of statistical approaches and apply the same to solve the real life problems in the fields of data science and apply the research-based knowledge to analyse and solve advanced problems in data science

This course is for individuals who...

This programme is for students who wish to learn about advanced data analytic methods that are currently available on the market. The training focuses on the development of skills and an understanding of how to properly use available data to gain superior insights. The course will concentrate on the models, tools, and procedures for analyzing data from a range of sources.

Students who are looking for...

A profession in a field that is always evolving, with an almost limitless range of data generation, gathering, processing, and analysis. Financial stability, the ability to relocate, and the opportunity to learn for the rest of one's life are just a few of the benefits that make this programme an excellent choice for computer science enthusiasts.

Successful graduates of the course will have access to a variety of career opportunities. The course's successful graduates are offered a preliminary average compensation of INR 3 to 8 Lacs, which is based on the candidate's experience in the field.

After completing the course, students might find work in both the commercial and public sectors.

Course Fee
For National Students
1st Year 110000 2nd Year 113300
For International Students
Fee Per Semester Fee Per Year
NA NA
Programme Structure

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

MDA101

Foundations of Data Science

4

0

-

4

4

2.

MMT104

Statistical Methods

4

0

-

4

4

3.

MDA102

Mathematics for Machine Learning

  4

0

-

4

4

4.

MDA103

Probability Theory and Distributions

4

0

-

4

4

5.

MDA104

Next Generation Databases

4

0

-

4

4

 

 

 

 

 

 

 

 

 

PRACTICALS

 

 

 

 

 

 

6.

MDA151

Practical -I (Based on Paper MMT104, MDA102 Using Excel/SPSS/Mini-tab)

-

-

3

3

2

7

MDA152

  Practical -II (Based on Paper MMT104, MDA102, 103, 104 UsingR/ Python)

-

-

3

3

2

 

 

 

 

 

 

 

 

TOTAL

15

-

6

26

24

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

MMT123

Numerical Methods  with Programming

4

0

0

4

4

2.

MDA105

Regression Analysis and PredictiveModels

4

0

0

4

4

3.

MDA106

Statistical Data Preparation& Analytics

4

0

0

4

4

4.

MDA107

Advanced Big Data and Text Analytics

4

0

0

4

4

5.

MDA108

Data Mining & Artificial Intelligence

4

0

0

4

4

6.

CCU401

Community Connect

-

-

2

2

2

 

PRACTICALS

 

 

 

 

 

 

7.

MDA153

Practical -III (Based on Paper MDA105, 106, 107UsingR/ Python/SAS/SPSS)

-

-

3

3

2

8.

MDA154

Practical -IV (Based on Paper MDA108UsingR/Python)

-

-

3

3

2

TOTAL

15

-

13

28

26

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1

MDA201

Inferential Statistics

4

0

0

4

4

2

MDA202

Multivariate Data Analysis

4

0

0

4

4

3

MDA203

Soft Computing Techniques

4

0

0

4

4

4

MDA204

Exploratory Data Analysis and Visualization

4

0

0

4

4

5

OPE XXX

Open elective (GE)

-

-

-

2

2

 

PRACTICALS

 

 

 

 

 

 

6.

MDA251

Practical -V (based on MDA 201 , MDA 202) (using SPSS/SAS/STRATA)

-

-

3

3

2

7.

MDA252

Practical -VI

(using based on MDA 203 , MDA 204)

-

-

3

3

2

TOTAL

12

-

10

22

22

S. No.

SUBJECT

CODE

Title of Paper

HOURS

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

MDAXXX

Elective-I (Online/Offline Courses)

4

0

0

4

4

2.

MDA XXX

Elective-II (Online/Offline Courses)

4

0

0

4

4

 

DISSERTATION

 

 

 

 

 

 

 

MDA253

Capstone project (Based on full time training program/internship program in any government/private institute or industry during last semester)

-

-

30

6 weeks (mini 30)

10

TOTAL

6

2

30

38

18

Programme Curricula
S.No. Academic year Curricula Link

1

2021-22 View Details
Eligibility Criteria
For National Students
  • B.Sc. IT/CS/Mathematics, BCA with minimum 50% marks
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
  • Research Scientist
  • Data Analyst
  • Data Scientist/Sr. Data Scientist
  • Business Intelligence Developer

Take the next step towards a career in basic sciences.

Apply Now