Do I need a coding background?

No. Python starts from first principles in year one.

How is this different from the BCA with Data Science and AI?

The BCA is a broader computing degree with a data specialisation. This B.Sc is narrower and goes further into analytics and generative AI specifically.

What can I study after this?

M.Sc in Data Science and AI, MCA, or an MBA in Business Analytics are all common next steps.

Information Technology & Applied Sciences

B.Sc (H) Data Analytics and Generative AI Powered by IBM

A cutting-edge AI learning course in Kolkata at the undergraduate level. Students master Generative AI, LLMs, data analytics, and IBM AI tools, equipping them for the next generation of AI-driven industries. One of the best AI courses in India for science graduates.

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Duration

4 Years

Eligibility

10+2 in any stream with Mathematics or Statistics as a subject

About the B.Sc (H) Data Analytics and Generative AI programme

An undergraduate degree built around where analytics is actually heading — classical data analysis in the first half, generative AI and large language models in the second. You learn to query, model and visualise data, then move on to prompt engineering, retrieval-augmented generation and building applications on top of foundation models. The IBM track supplies the tooling.

Why study B.Sc (H) Data Analytics and Generative AI at TIU

Generative AI as core curriculum

LLMs, prompting, fine-tuning and RAG are full modules, not a guest lecture.

Analytics foundation first

You learn statistics and SQL before touching foundation models, so the AI work rests on something solid.

Build and deploy LLM applications

Coursework includes shipping a working AI application, not only calling an API in a notebook.

Responsible AI module

Bias, hallucination, evaluation and governance are taught as engineering problems.

What you study, year by year

Year 1— Data foundations

Programming with PythonStatistics & ProbabilityDatabase Systems and SQLData VisualisationMathematics for Data Science

Year 2— Analytics core

Exploratory Data AnalysisMachine Learning FundamentalsBusiness AnalyticsData Wrangling & ETLPredictive ModellingDashboarding with Power BI

Year 3— Generative AI

Deep Learning FoundationsNatural Language ProcessingLarge Language Models & TransformersPrompt EngineeringRetrieval-Augmented GenerationIBM watsonx Application Development

Year 4— Advanced practice, internship and project

Fine-Tuning & Model EvaluationAI Agents and AutomationResponsible & Explainable AIIndustry InternshipMajor Project

Indicative structure. Module sequencing may vary by batch and regulatory guidelines.

Tools and platforms

What you'll work with

PythonSQLIBM watsonxHugging FaceLangChainPower BIpandasVector databases

Who this programme suits

Students who want to work with generative AI as builders rather than users
Anyone drawn to analytics but wanting the newest layer of the field as well
Students from any 10+2 stream with a mathematics or statistics background

Where this degree takes you

Roles graduates target

AI EngineerML ResearcherData ScientistNLP Specialist

Industries that hire

AI product companiesAnalytics consultingMarketing and content technologyFintechEnterprise automation

B.Sc (H) Data Analytics and Generative AI: common questions

The specific models will change; the underlying skills — evaluation, retrieval, data quality, deployment — transfer. That is why the first two years are spent on analytics fundamentals rather than on today's tooling.

Admissions for 2026 are open

Talk to the admissions team about eligibility, scholarships, and the application timeline for B.Sc (H) Data Analytics and Generative AI Powered by IBM.

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