Choose your batch
Each batch has its own dates, timing and fee. Pick one to see its details and book.
Live weekend classes
AI & Data Science Program
Live weekend classes and 12 industry projects, from your first line of Python to job-ready AI engineering.
- 12 months
- Sundays
- 3 hours a week
- 12 industry projects
- 14 industry tracks to choose from
- Beginner → Advanced → Expert
Learn AI and data science on weekends, alongside college or work. Every month you learn one area in live classes and finish an end-to-end project on real industry data, so by the end you have 12 projects to show employers. Classes are live and recorded, taught by industry practitioners, in small batches.
Fees
Monthly
₹2,999 / month
Pay each month (UPI AutoPay or card). Cancel any time; access runs to the end of the paid month.
One-time
₹32,390 for 12 months
The whole program, plus recordings of earlier batches.
How joining works
-
1
Book a free seat
No payment now. Your seat is held in the next batch.
-
2
Pay when the batch is confirmed
We email you; pay within 48 hours to keep your seat.
-
3
Join live weekend classes
Classes are recorded, so you can catch up on anything you miss.
Choose your industry track
Everyone learns the same AI skills each month. Your 12 projects come from the industry you choose, so you finish with a portfolio for the jobs you want.
Insurance: AI prices policies, settles claims faster, flags suspicious claims and predicts which customers will renew.
Free courses and datasets for Insurance →Month by month
Every month ends with an end-to-end project you can show employers, from Insurance.
Month 1 Python for data Beginner
Python basics, data types, loops and functions; working with files, CSV and JSON; virtual environments, Jupyter and Git.
Project · Insurance
Policy register cleaner
Clean a messy policy register (dates, premiums, duplicates) and summarise the portfolio by product and city.
Month 2 Data analysis with pandas and SQL Beginner
pandas DataFrames, cleaning and joining data, group-by and pivot tables; SQL queries, joins and window functions.
Project · Insurance
Claims analysis in SQL
Analyse claims by product, region and settlement time, and calculate claim settlement ratios like those IRDAI publishes.
Month 3 Statistics and data visualisation Beginner
Descriptive statistics, probability, sampling, hypothesis tests and A/B testing; charts with Matplotlib, Seaborn and Plotly.
Project · Insurance
Motor claims statistics
Study how often and how much motor policies claim, and test whether younger drivers really claim more.
Month 4 Machine learning foundations Beginner
Supervised learning, regression and classification, train/test splits and cross-validation, scikit-learn pipelines.
Project · Insurance
Health premium predictor
Predict health insurance costs from age, BMI, smoking and region with regression models.
Month 5 Feature engineering and model evaluation Advanced
Feature engineering, imbalanced data, ensembles (random forests, XGBoost, LightGBM), metrics, explainability with SHAP.
Project · Insurance
Claim fraud detection
Flag the few fraudulent claims among many honest ones with gradient boosting, and explain each flag with SHAP.
Month 6 Deep learning with PyTorch Advanced
Neural networks, training loops, CNNs for images, transfer learning, GPUs on Google Colab.
Project · Insurance
Vehicle damage assessment
Train an image model that finds the damaged part of a car in a photo and rates the damage as minor, moderate or severe.
Month 7 Natural language processing Advanced
Text cleaning, embeddings, transformers and Hugging Face, fine-tuning for classification, multilingual models.
Project · Insurance
Claim document extractor
Pull the patient, hospital, dates and amounts out of hospital bills and claim forms with NLP.
Month 8 Time series and forecasting Advanced
Trends and seasonality, ARIMA and Prophet, gradient-boosted forecasts, evaluating forecasts over time.
Project · Insurance
Claims volume forecast
Forecast monthly claims, including monsoon and festival effects, so the claims team can plan staffing.
Month 9 Large language models and RAG Expert
How LLMs work, prompting, embeddings and vector databases, retrieval-augmented generation, evaluating answers.
Project · Insurance
Policy wording assistant
Build a RAG assistant that answers "am I covered?" from policy documents and quotes the clause it relied on.
Month 10 AI agents and tool use Expert
Function calling, multi-step agents, planning and memory, guardrails and evaluation of agent behaviour.
Project · Insurance
Claims triage agent
Create an agent that reads a new claim, checks the policy, asks for missing documents and routes it to the right desk.
Month 11 MLOps and deployment Expert
APIs with FastAPI, Docker, CI/CD, model registries, monitoring and data drift, cloud deployment basics.
Project · Insurance
Pricing model in production
Deploy the premium model with versioning, automated tests and monitoring, so every quote can be traced to a model.
Month 12 Capstone and career preparation Expert
Scoping a real problem, project planning, portfolio, résumé and GitHub reviews, mock technical interviews.
Project · Insurance
Insurance capstone
Solve a real insurance problem end to end, such as renewal prediction or faster claims, and present it to a panel.
What you can watch
| Monthly | Your batch's live classes and recordings, from the batch start to the current month, while your payments are up to date. |
|---|---|
| One-time | Your whole batch, plus recordings of earlier batches. |
| Joining a running batch | That batch's earlier recordings, so you can catch up. |
| After you finish | 12 more months of free access. |