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Data & AIBeginner to Advanced
Data Analytics, Data Science & Data Engineering (AI-First)
One full year that takes you from spreadsheets to shipping real AI products. You cover the analyst, data engineering and data science stack the way working teams use it in 2026, with a heavy focus on LLMs, RAG and AI agents. Classes run 2 to 3 times a week with live projects, and your fee is decided by how you do in the entrance test.
1 Year Beginner to Advanced 24 modules
What you get
Analyst, Engineer & Scientist in one track
2 to 3 live classes per week
Hands-on LLMs, RAG & AI agents
Modern data stack + MLOps/LLMOps
Scholarship decided by entrance test
End-to-end capstone + job portfolio
Where this takes your career
Become job-ready across analytics, data engineering and AI. You ship real data pipelines, models and LLM apps, which is exactly what hiring teams test for in 2026.
Roles you can target
Data Analyst ₹5-10 LPA
Data Engineer ₹8-18 LPA
Data Scientist ₹8-20 LPA
AI / ML Engineer ₹10-25 LPA
Salary figures are typical India market ranges (2026) for the role, not a guarantee.
Internship pathway
Your capstone is an end-to-end AI data product. Top performers move into a live-project internship, and everyone gets portfolio reviews, mock interviews and referrals.
Scholarship by entrance test
Your fee is not fixed. Take the AI-generated entrance test and your score decides your tuition waiver, from full fee down to only the ₹3,500 admission fee.
| Marks (of 20) | Tuition waiver | You pay |
|---|---|---|
| 20 | 100% | ₹3,500 |
| 17-19 | 75% | ₹18,875 |
| 13-16 | 50% | ₹34,250 |
| 9-12 | 25% | ₹49,625 |
| 0-8 | 0% | ₹65,000 |
Full syllabus
- 01Foundations: Python for Data (pandas, Polars, NumPy)
- 02Foundations: SQL and Analytics Engineering with dbt
- 03Foundations: Statistics, Probability and Experiment Design
- 04Analytics: Data Cleaning, EDA and Decision Storytelling
- 05Analytics: AI-assisted BI with Power BI and Tableau
- 06Analytics: Automating Reports and Spreadsheets with AI Copilots
- 07Engineering: Data Modeling and Cloud Warehousing (BigQuery, Snowflake)
- 08Engineering: ELT and the Modern Data Stack (Airbyte, dbt, Dagster)
- 09Engineering: Real-time and Streaming Pipelines (Kafka, Spark)
- 10Engineering: Lakehouse with Delta Lake and Apache Iceberg
- 11Engineering: Data Quality, Governance and Observability
- 12Science: Machine Learning and Feature Engineering (scikit-learn)
- 13Science: Deep Learning with PyTorch
- 14Science: Time Series Forecasting
- 15Science: NLP and Computer Vision Essentials
- 16Generative AI: Large Language Models, Prompting and Fine-tuning
- 17Generative AI: Retrieval-Augmented Generation with Vector Databases (pgvector, Qdrant)
- 18Generative AI: AI Agents, Tool Use and Orchestration
- 19Generative AI: Building Products on the Cehpoint AI API
- 20Production: MLOps and LLMOps (MLflow, model serving, monitoring, cost control)
- 21Production: Shipping AI Data Apps with FastAPI and Streamlit
- 22Responsible AI, Privacy and the India DPDP Act
- 23Capstone: End-to-End AI Data Product (ingest, warehouse, model, LLM app, dashboard)
- 24Career: Kaggle, GitHub Portfolio, Interviews and Freelancing