Bachelor's degreeOnline · live classesOn campus
BSc Data Science
Learn to turn raw data into decisions — statistics, machine learning, data engineering and analytics, from the ground up.
Apply nowApproved & recognised by the University of Mysore
Duration
3 years · 6 semesters
Credits
180 credits
Time commitment
15–20 hrs/week
Intakes
Rolling admissions — multiple intakes per year
About this programme
A three-year undergraduate degree covering the full data lifecycle: collecting and managing data, analysing it with statistics and machine learning, and communicating results that drive business decisions. You start with programming and mathematics from first principles, then progress through analytics, big data systems and model deployment, finishing with an internship and a bachelor thesis on a real dataset.
What you'll learn
Write production-quality Python and SQL for data work
Apply statistical thinking: probability, inference and experiment design
Build and validate machine learning models on real datasets
Engineer data pipelines and work with big data and cloud platforms
Create visualisations and dashboards that communicate clearly to non-experts
Handle data responsibly: privacy, governance and ethics
Curriculum
Semester 1
Foundations- Introduction to Data Science
- Introduction to Programming with Python
- Mathematics I: Analysis
- Statistics I: Probability & Descriptive Statistics
- Academic Skills & Collaborative Work
Semester 2
Working with data- SQL & Relational Databases
- Mathematics II: Linear Algebra
- Statistics II: Inferential Statistics
- Data Wrangling & Exploratory Analysis
- Data Visualisation
Semester 3
Machine learning & analytics- Machine Learning
- Business Analytics
- Data Management & Warehousing
- Mathematical Modeling
- Data Ethics & Privacy
Semester 4
Scale & depth- Deep Learning Fundamentals
- Big Data Technologies (Spark & distributed systems)
- Data Engineering & Pipelines
- Time Series Analysis & Forecasting
- Project: End-to-End Analytics
Semester 5
Advanced topics & electives- Cloud Computing for Data Science
- Elective: NLP / Computer Vision / Recommender Systems
- Model Deployment & MLOps
- Project: Data Product
Semester 6
Internship & thesis- Industry Internship (supervised placement)
- Bachelor Thesis
- Thesis Colloquium (defence)
Careers this prepares you for
Data ScientistData AnalystData EngineerBusiness Intelligence AnalystMachine Learning Engineer
Admission requirements
- Completed higher secondary education (12th grade / A-levels or equivalent)
- English proficiency (instruction is in English)
- No prior programming experience required — Semester 1 starts from scratch