B. Sc. (Hons.) (Data Science)

The b. Sc. In data science is an exciting programme that aims to build a broad foundation in mathematics, statistics, and computer science among students, through which they can learn a wide variety of analytics applications in science, engineering, technology, and the arts (seta). 

• The programme is application-focussed so that as students learn about mathematical, statistical, and computational tools and techniques, they continuously get to apply their learnings in a wide variety of domains.
• The programme aims to attract hard-working and aspiring students who have the curiosity to learn new mathematical, statistical, and computational techniques, the ability to envisage and develop analytics solutions, the ability to extract insights from the analytic models, and the ability to communicate and collaborate with domain experts to improve/optimize systems. The subjects that students take include traditional branches of mathematics and statistics such as algebra, analysis, differential equations, descriptive statistics, inferential statistics, and R and Python programming, but also several cutting-edge offerings such as visual analytics, descriptive analytics, predictive analytics, prescriptive analytics, machine learning, deep learning, and artificial intelligence.
• The programme aims to mold the students to become data science leaders of the future, to be able to creatively apply mathematical, statistical, and computational approaches to solve complex and challenging problems in Science, Engineering, Technology, and the Arts.

Special Features

• Have an inside track to Global Leaders’ Alliance Fellowship
• Take classes with Oxbridge/Ivy League faculty
• Broad foundation in mathematics, statistics, and computer science
• Learning a wide variety of analytics applications in Science, Engineering, Technology, and the Arts (SETA)
• Internships in industry and academia, with live analytics projects
• Contributing to and organising seminars and conferences

Programme Structure
Core

• Basic Statistics & Probability Theory
• Advanced Calculus
• Linear Algebra & Matrix Theory
• Statistical Inference
• Numerical Methods
• Basic Programming & Algorithms using Python
• Descriptive Analytics & Data Visualisation
• Machine Learning using Python
• Data Warehousing
• Big Data Analytics

Electives

• Operations Research
• Regression Analysis/Modelling
• Mathematical Modelling
• Discrete Mathematics & Combinatorics
• Time Series Analysis and Forecasting
• Fuzzy Logic and Analysis
• Simulation Modelling
• Advanced Numerical Methods
• Predictive Analytics using R & Python
• Artificial Intelligence & Neural Networks
• Reliability and Survival Analysis
• Data Mining
• Cryptography & Blockchain
• Econometrics
• Supervised & Unsupervised Learning
• Spark Programming
• Deep Learning
• Natural Language Processing

Eligibility

• 10+2 from recognized Board / Council with minimum 50% aggregate marks with Mathematics / Computer Science as Compulsory Subject.
• A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC / ST.