The academic track of the Bachelor of Data Science (BDS) program is made of a blend of core and advanced specialist subjects. Our curriculum is built on the principle that subjects get more and more specialised as you progress through the program.


The subjects undertaken in the first year of the program build a strong foundation in data science, math and computer science.

Credit Courses

  • Discrete Mathematics
  • Mathematical Statistics
  • Introduction to Computer Programming
  • Introduction to Databases
  • Linear Algebra
  • Calculus
  • Introduction to Data Science
  • Statistical Data Analysis

Non-Credit Skill Development Courses

  • Linux
  • HTML5/CSS3
  • Ajax, jQuery, XML, mySQL, JSON, RestAPI, JavaScript
  • Node.js, Facebook-React.js
  • Introduction to Java/Advanced Java
  • Introduction to Data Structures & Algorithms in Java
  • Basics of Cloud Computing, AWS, Docker, Google-Kubernetes, Istio, Calico

You will also get the opportunity to participate in graduate-level projects / discussions / workshops / industry colloquiums.

Your study in Year 1 will enable you to have a CV strong enough to be selected for coding challenges and empower you with skills to excel in that.



In the second year, mathematical and analytical topics are explored in considerable depth and students are exposed to topics such as Data Integration, Data Structures, Programming for Analytics, Machine Learning, and Matrix Algebra and Applications.

  • Advanced Calculus
  • Algorithms and Data Structures
  • Data Integration and Warehousing
  • Visual Analytics (or Explorative data analysis)
  • Matrix Algebra and Applications
  • Programming for Analytics
  • Consumer Behaviour and Marketing Research
  • Machine Learning


We encourage students to partake in internships. In Year 2, between semesters 4 & 5, students have a winter break of nearly 4 months. The skills students have developed will enable them to apply for internships in companies like Google, Facebook, Amazon, Microsoft, Palantir, SAP, Oracle, Goldman Sachs, JP Morgan and SAS. SP Jain will work with students to help place them in relevant firms for an internship. This can't be guaranteed but is a priority to help all students achieve this. 



Advanced learning continues in Year 3 through topics such as Data Mining, Social Web Analytics, and Big Data Processing Techniques and Platforms.

  • Simulation Modelling
  • Data Mining
  • Object Relational and NoSQL Databases
  • Data Science Capstone Project I
  • Social Web Analytics (or Web, Internet of Things and Social Media Mining)
  • Advanced Analytics (Stream, Sensor and Spatio-temporal Analysis)
  • Big Data Processing Techniques and Platforms
  • Data Science Capstone Project II


In the third and final year, students undertake applied analytics capstone projects that give them practical and hands-on experience in identifying and interpreting actionable information from raw data and using them to make informed and mathematically valid decisions.



A specialised new area of data science is emerging – Neuromorphic Computing. Companies like IBM (True North), NVDIA, Amazon (AWS DeepLens) are launching specialised AI-on-Chip products, and our BDS students will get to undertake a project in this area.