School of Engineering and Technology
B.Tech (Data Science)
A programme built for the age of data – covering the full data pipeline from ingestion to business intelligence, with a strong statistical and computational foundation, and domain electives across healthcare, finance, and enterprise analytics.
About the Programme
Data scientists are the most sought-after professionals of this decade – and this programme trains students to be exceptional ones. The curriculum covers the mathematical foundations of statistical inference, the engineering challenges of big data pipelines, and the domain expertise needed to turn numbers into decisions. Students work with real datasets every semester – Kaggle, government open data, and industry-provided datasets from partner companies. Graduates emerge with a portfolio of end-to-end data projects, proficiency in Python and R, and certifications from Databricks, Tableau, or AWS.
Programme Details
Course at a Glance
180
8 Semesters
Data Science
60
Engineering and Technology
Programme Structure
YEAR I - DATA FOUNDATIONS
Statistics, Python, and SQL
Statistics and Probability · Python for Data Science ·SQL and Databases · AI Literacy · Data Visualisation Fundamentals · Communication Skills · Human Values
YEAR II - DATA ENGINEERING
Building data pipelines
R for Statistical Computing · Data Structures and Algorithms · Machine Learning · Big Data Technologies (Hadoop, Spark) · DBMS and NoSQL · Data Warehousing · Business Analytics Fundamentals
YEAR III - ADVANCED ANALYTICS
From data to decisions
Deep Learning for Tabular Data · Time Series Analysis · NLP for Data Science · Cloud Data Platforms · Data Engineering at Scale · 2 Domain Electives · Internship (mandatory)
YEAR IV - CAPSTONE
Portfolio and professional launch
Capstone Data Science Project (two semesters) · Advanced Electives · Research Methods · Data Ethics and Privacy · Business Communication for Data Scientists
Specialisations - 5 Tracks
BUSINESS INTELLIGENCE AND VISUALISATION
Tableau · Power BI · Executive Dashboards · KPI Design · Data Storytelling
BIG DATA ENGINEERING
Apache Spark · Kafka · Hadoop · ETL Pipelines · Data Lakes · Apache Airflow
HEALTHCARE ANALYTICS
Clinical Data · Electronic Health Records · Epidemiology · Drug Trial Analytics
FINANCIAL ANALYTICS
Risk Modelling · Fraud Detection · Quantitative Finance · Regulatory Data
AI AND PREDICTION
Forecasting · Recommendation Systems · Anomaly D · Auto ML
Themes
Full Data Science Stack
From data collection and cleaning (pandas, SQL) through analysis (R, scipy) to deployment (FastAPI, Streamlit). Students graduate with end-to-end project experience on real data.
Real datasets every semester
No synthetic problems. Every semester includes a project on real-world datasets from Kaggle, government open data portals, and industry partners. Portfolio-building from I Year.
Data ethics as a core subject
Data privacy, DPDPA 2023, GDPR, algorithmic bias, and fairness are taught as core subjects—not optional modules. Responsible data use is non-negotiable.
Eligibility Criteria
| Criterion | Requirement |
|---|---|
Qualifying exam | 10+2 (Class XII) from any recognised board |
Mandatory subjects | Physics, Chemistry, Mathematics (PCM) |
Minimum marks | 10+2 with a minimum 55%, including Physics, Chemistry and Mathematics |
Entrance exam | Valid JEE Main score OR Metro University MET |
Preferred | Students with strong Mathematics background, computing interest, or Olympiad exposure |
Selection | JEE Main / MET → Counselling → Seat allotment |
Frequently Asked Questions
Is programming heavy in this programme?
Yes – Python (Pandas, NumPy, Scikit-Learn, PySpark) and R are both used extensively. Strong programming skills are developed from I Year.
What is the difference from B.Tech CSE (AI & ML)?
Data Science covers the full data lifecycle – collection, storage, processing, analysis, and insight. AI and ML focuses on building AI models. Data Scientists often feed and evaluate the models AI/ML engineers build.
Will I learn SQL and database systems?
Yes – SQL, NoSQL (MongoDB, Cassandra), cloud databases (AWS RDS, BigQuery), and data warehousing (Snowflake) are all part of the curriculum.
What is the average placement?
Average salary: Rs 7.2 LPA. Top recruiters: Accenture Analytics, EXL Analytics, Mu Sigma, Flipkart, and data-focused startups. Highest offer: Rs 18 LPA.