B.Sc. (Hons.) Data Sciences and Analytics

The b. Sc(hons) data sciences and analytics program enables students to engage in the domains of data mining, analysis, and predictive modelling. The programme’s curriculum has more of application-oriented learning and the curriculum mainly stresses on the mastery of basic mathematics, statistics, and computer science. 

• The emphasis of the programme is to expose students to advanced concepts, developments, and techniques in the realm of data analytics.
• The B.Sc(Hons) Data Sciences and Analytics Program is developed by the members of the faculty based on interactions with various universities, financial institutions, and industries. The curriculum is outcome based and it imbibes required theoretical concepts and practical skills in the domain. By undergoing this programme, students develop application-oriented learning skills, critical, analytical thinking, and problem-solving abilities for a smooth transition from academic to real-life work environment. Students are trained in communication skills and interdisciplinary topics to enhance their scope.

Program Objectives

• To disseminate knowledge and skills through instructions, teaching, training, seminars, workshops and symposia in Engineering and Technology, Art and Design, Management and Commerce, Health and Allied Sciences, Physical and Life Sciences, Arts, Humanities and Social Sciences to equip students and scholars to meet the needs of industries, business and society
• To generate knowledge through research in Engineering and Technology, Art and Design, Management and Commerce, Health and Allied Sciences, Physical and Life Sciences, Arts, Humanities and Social Sciences to meet the challenges that arise in industry, business and society
• To promote health, human well-being and provide holistic healthcare
• To provide technical and scientific solutions to real life problems posed by industry, business and society in Engineering and Technology, Art and Design, Management and Commerce, Health and Allied Sciences, Physical and Life Sciences, Arts, Humanities and Social Sciences
• To instill the spirit of entrepreneurship in our youth to help create more career opportunities in the society by incubating and nurturing technology product ideas and supporting technology backed business
• To identify and nurture leadership skills in students and help in the development of our future leaders to enrich the society we live in
• To develop partnership with universities, industries, businesses, research establishments, NGOs, international organizations, governmental organizations in India and abroad to enrich the experiences of faculties and students through research and developmental programmes

Semester I

• Compulsory Foundation Course 1 (CFC 1) 4
• Compulsory Foundation Course 1 (CFC 2) 4
• Linear Algebra (CC) 5
• Programming in R Lab (CC) 5
• Data Visualization (CC) 5
• Ability Enhancement Course 1 3

Semester II
Course Credits

• Compulsory Foundation Course 3 (CFF 3) 4
• Compulsory Foundation Course 4 (CFF 4) 4
• Inferential Statistics (CC) 5
• Regression Techniques and Time Series Analysis (CC) 5
• Python Programming Lab (CC) 5
• Generic Elective 1 3
• Skill Enhancement Course – 1 (SEC-1) 2

Semester III
Course Credits

• Multivariate Analysis (CC) 5
• Database Management Systems (CC) 5
• Data Pre-processing (CC) 5
• Generic Elective 2 3
• Ability Enhancement Course 1 3

Semester IV
Course Credits

• Operations Research & Optimisation Techniques ion Techniques (CC) 5
• Data Warehousing & Mining (CC) 5
• Artificial Intelligence (CC) 5
• Generic Elective-3 3
• Skill Enhancement Course – 2 (SEC-2) 2

Semester V
Course Credits

• Machine Learning (CC) 5
• Big Data (CC) 5
• Basic Econometrics(DSE)( Track 1) 4
• Advanced Time series and Regression techniques (DSE) (Track 2) 4
• Open Elective-1 (SSS) 3

Semester VI
Course Credits

• Dissertation/Project (CC) 6
• Deep Learning (DSE) (Track 1) 4
• Supply chain management(DSE)(Track 2) 4
• Open Elective-2 (SSS) 3

Semester VII
Course Credits

• Cloud Computing (DSE) 4
• Advanced Statistics (DSE) 4
• Natural language Processing(DSE) (Track 1) 4
• Applied Econometrics (DSE) (Track 2) 4
• Applications in Economics (DSE) (Tack 2) 4
• Consumer Behavior (DSE) (Tack 2) 4
• Open Elective-3 (SSS) 3

Semester VIII
Course Credits

• Capstone/project/ Internship 20

Career Path
Pave Your Way to a Data-driven Career

• Data Scientist
• Business Intelligence Analyst
• Data Analyst
• Applications Architect
• Machine Learning Engineer
• Market Research Analyst
• Database Administrator