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Bachelor of Science- Data Science & Analytics

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Bachelor of Science- Data Science & Analytics

Sharda School of Basic Sciences & Research (SBSR)

  • Programme Code

    SBR0308

  • Level

    Graduate

  • Duration

    3 Years

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About the Programme

Programme Educational Objectives (PEO’s)

  • PEO1: Prepare professionals conversant with current and advanced technological   tools to carry out Investigation, analysis and synthesis by identifying various   compute oriented solutions.
  • PEO2: To develop positive attitude and skills which enable them to become a   multi facet personality.
  • PEO3: To prepare students in such a way so that they perform excellently in   national label entrance examinations conducted by various well known institution   like IIT’s/ central Universities/other academic institutes etc. to pursue their   PG/MS/Dual PG and Ph. D. programs.
  • PEO4: To make them aware of effective machine learning and Artificial   Intelligence based data analytics and inference required for Industrial Application.
  • PEO5: To inculcate passion for lifelong learning by introducing principles of   group dynamics, public policies, environmental and societal context.

Program Outcomes (PO’s)

  • PO1: Data Science knowledge: Application of Data Science knowledge in   various fields of science, engineering and management etc.
  • PO2: Nature of Data Science: Understand the concise, precise and rigorous   nature of Data Science.
  • PO3: `Critical thinking: Develop the skill to think critically on abstract concepts   of Data Science.
  • PO4: Problem analysis: Develop the ability to analyze a problem logically and   dissect into micro-parts and thus resolving the problem to accessible components.
  • PO5: Presentation skill: Develop the skill to pleasant exposition for successful   presentation for any career interview with confidence.
  • PO6: Data Science logic: Formulates and develops data analysis arguments in   logical manner.
  • PO7: Team Work: Work as a team player and strive for self-excellence.
  • PO8: Ethics: Realize and understand professional, ethical and cultural   responsibilities.
  • PO9: Communication: Communicate effectively with an elite audience.
  • PO10:Life-long learning: Engage in life-long learning towards enduring professional development

Course Fee
For National Students
1st Year 110000 2nd Year 113300 3rd Year 116699
For International Students
Fee Per Semester Fee Per Year
NA 3400*
Programme Structure

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

MSM 101

Foundation course in Mathematics

3

1

0

4

4

2.

MSM 312

Discrete  Mathematics

3

1

0

4

4

3.

BDA 101

Statistics I

3

0

1

5

4

4.

EVS106

Environmental Science

3

0

0

3

3

5.

ARP 101

Communicative English I

1

0

1

3

2

6.

BDA 103

Fundamentals of Computers & Problem solving  using C

2

0

1

4

3

7.

BDA104

Programming R

2

0

1

4

3

TOTAL

17

2

4

27

23

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1

MSM106

Linear Algebra

3

1

0

4

4

2

BDA102

Statistics II

3

0

0

3

3

3

BDA105

Statistics III

3

0

1

5

4

4

BDA107

Differential Equations & Complex Variable

3

1

0

4

4

5

BDA108

Introduction to Computer organization

3

0

0

3

3

6

BDA110

Data Structure & Algorithms

3

0

1

5

4

7

BDA 111

Introduction to MATLAB in Data Analysis

2

0

2

5

4

 

TOTAL

20

2

4

29

26

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

MSM 213

Numerical Analysis

3

0

1

5

4

2.

BDA 201

Data preparation and Data  Cleaning

3

0

1

5

4

3.

BDA202

Database Management Systems

3

0

1

5

4

4.

BDA205

Data Ware housing and Data mining

3

0

1

5

4

5.

        BDA 204

  Operating Systems

3

0

1

5

4

  6.

BDA 211

Oops using Python

2

0

1

4

3

  7.

CCU 401

Community Connect

0

0

2

2

2

TOTAL

17

0

8

31

25

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

BDA203

Text Analytics

3

0

1

5

4

2.

BDA206

Regression, time series, forecasting and Index numbers

3

0

1

5

4

3.

BDA207

Multivariate Analysis

3

0

1

5

4

4.

BDA208

Statistical Inference (non- parametric)

3

0

1

5

4

5.

BDA209

Recommender Systems

3

0

1

5

4

6.

BDA210

Data Visualization

3

0

1

5

4

TOTAL

18

0

6

30

24

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

BDA301

Statistical Analysis (Count Data and survival Analysis)

3

0

1

5

4

2.

BDA302

Data Scientist Toolbox

3

0

1

5

4

3.

BDA303

Machine learning

3

0

1

5

4

4.

BDA 304

Statistical Simulation

3

0

1

5

4

5.

MSM315

Operational Research

3

1

0

4

4

6.

XXXX

Elective-I

3

0

1

5

4

TOTAL

18

1

5

29

24

S. No.

SUBJECT

CODE

Title of Paper

Teaching Load

CREDITS

 

THEORY

 

 

 

 

 

 

L

T

P

TOTAL

 

1.

BDA305

Deep Learning

3

0

1

5

4

2.

BDA306

Big Data Analytics

3

0

1

5

4

3.

XXX

Elective-II

3

0

1

5

4

4.

XXX

Elective-III

3

0

1

5

4

5.

BDA307

Capstone project

6

0

0

6

6

6.

BDA308

Research report writing and Presentation

0

0

2

3

2

TOTAL

18

0

6

29

24
Eligibility Criteria
For National Students
  • Sr. secondary (10+2) with minimum 55% marks in PCM/PCB/Humanities with Maths or Applied Maths/Commerce with Maths or Applied Maths
  • Proficiency in English communication
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.

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