B.Sc. (Hons.) in Statistics and Data Analytics

Eligibility

Minimum 50% aggregate in 10 +2 or equivalent from any recognized board with Mathematics/Statistics

Duration

3 Years

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[vc_row][vc_column][ult_tab_element tab_style="Style_4" tab_animation="Slide-Horizontal" acttab_background="#005aab" enable_bg_color="#fcfcfc" container_border_style1="border-style:none;|border-radius:1px;|border-color:#e8e8e8;"][single_tab title="B.Sc. (Hons) in Statistics and Data Analytics" tab_id="1624353455451-1-10"][ultimate_heading main_heading="B.Sc. (Hons) in Statistics and Data Analytics " main_heading_margin="margin-top:20px;" sub_heading_margin="margin-bottom:20px;"][/ultimate_heading][vc_empty_space][vc_column_text]Introduction to the Program:

This course has been frame out on the based on fundamental of Statistics and its use in data analytics with the aim that student under this course enriched by the core of modern data analytics that turn data into intelligence to inform decision-making and solve challenging problems. Applications range from economics and medicine, to social and environmental sciences. This degree covers theoretical and applied elements of modern statistics, and provides training and practical experience in modelling, analyzing and interpreting real data required in the economy, industry and research. The early years of the degree cover basic mathematics, probability and statistics. The final years focus on advanced specialist topics in statistical modelling, data science, machine learning, probability and stochastic processes.[/vc_column_text][vc_column_text]Program Educational Objective:

PEO 01: Graduate will equip with latest techniques in Data Analytics like Python, Machine learning, Big Data etc.

PEO 02: Graduates will able to choose their course as a training ground to develop their positive attitude and skills.

PEO 03: Graduates of the program will become technically competent to pursue higher studies.

PEO 04: Graduates are prepared to survive in rapidly changing technology and engage in life-long learning.

PEO 05: Graduates will communicate effectively in both verbal and written form in industry and society.[/vc_column_text][vc_column_text]Program Outcome:

PO 01: Academic Excellence: Understanding the academic field of Statistics and its different learning areas with applications.

PO 02: Contextualized Understanding: Develop the ability to distinguish between random and non-random experiments and simultaneously learn the theory and applications of probability

PO 03: Design/development of solutions: Identify, design and solve scientific problems based on data collection, data interpretation and analysis of results.

PO 04: Conduct investigations of complex problems: Explore various real-life problems and ways to solve them with a reliable solution using various statistical methods and tests.

PO 05: Quantitative Aspects: Learn to apply the tools of the various statistical and mathematical procedures with programming to solve real-life problems involving large data sets.

PO 06: Modernization and Tools Usage: Develop the ability in using modern statistical, mathematical and data analytics tools for design and analysis, and quality control.

PO 07: Societal Implication: Apply statistical methods and tools in societal, demographic, health, business and cultural issues

PO 08: Environment and Sustainability: Understand the tools towards problem solving and applications in biological science, agricultural science, and social sciences

PO 09: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of mathematical and data science.

PO 10: Individual and Team Work: Work effectively as an individual or as a member or leader in undertaking projects, research organizations, industries and multidisciplinary area

PO 11: Communication: Build up communication skills, both written and oral, so as to apply them to write effective reports.

PO 12: Life Long Learning: Develop the ability to evaluate theories, methods, principles, and applications of pure and applied Statistics and data science[/vc_column_text][vc_column_text]Programme Specific Outcome:

PSO 01: Have the versatility to work effectively in a broad range of analytic, scientific, government, financial, health, technical and other positions.

PSO 02: Be familiar with a variety of examples where the knowledge of mathematics or statistics helps to explain the abstract or physical phenomena accurately.

PSO 03: Enhance theoretical rigor with technical skills which prepare students to become globally competitive to enter into a promising professional life in both government and private sector[/vc_column_text][vc_column_text]Programme Eligibility:

Minimum 50% aggregate in 10 +2 or equivalent from any recognized board with Mathematics/Statistics

Duration (in Year): 3

 

Career Avenues:

  • There is scope in Banking, Finance institutions, R&D firms, Actuarial Science etc.
  • Federal bank, Cognizant, IBM, Infosys, Wipro, Deloitte, HDFC Bank, Google, etc. are some of top recruiters of the field.
  • A candidate may also pursue bureaucrat jobs like ISS, IES and IAS.
  • There is demand in urban planning companies of both government and private types.
  • This course plays a huge role in getting through the fields of risk assessment and management.
  • A candidate may also pursue for higher degrees and opt for teaching jobs in colleges or universities.

[/vc_column_text][vc_empty_space][vc_row_inner][vc_column_inner][vc_column_text]LIST OF ‘DISCIPLINE SPECIFIC ELECTIVE PAPERS (DSE)’ OFFERED BY THE DEPT. OF MATHEMATICS:

 

List of Elective Papers

Electives

Paper Name

Paper Code

Credit

L-T-P

DSE I

ECONOMETRICS

ECO11504

4

3-1-0

STATISTICAL QUALITY CONTROL

SDS11086

4

3-1-0

SOFT COMPUTING

MTH11038

4

3-1-0

DESIGN AND ANALYSIS OF ALGORITHM

CSE11659

4

3-1-0

 

 

DSE II

 

 

DEMOGRAPHY AND SURVIVAL ANALYSIS

SDS11087

4

3-1-0

INTRODUCTION TO BIG DATA

CSE11652

4

3-1-0

INTRODUCTION TO FINANCIAL RISK ANALYTICS

SDS11088

4

3-1-0

ACTUARIAL STATISTICS

SDS11037

4

3-1-0

DSE  III

 

INTRODUCTION TO DEEP LEARNING

CSE11653

4

3-1-0

INTRODUCTION TO  DEEP LEARNING     PRACTICAL

CSE12654

2

0-0-3

DATA MANIPULATION AND DATA CLEANING IN R 

SDS11030

4

3-1-0

DATA MANIPULATION AND DATA CLEANING IN R PRACTICAL

SDS12031

2

0-0-3

SURVEY SAMPLING 

SDS11089

4

3-1-0

SURVEY SAMPLING PRACTICAL

SDS12090

2

0-0-3

INTRODUCTION TO NUMERICAL ANALYSIS

MTH11017

4

3-1-0

NUMERICAL ANALYSIS LAB

MTH12019

2

0-0-3

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