Phase 1 · Day 1–10
Foundations
Python + data fluency
- Python for data: typing, libraries, environments
- NumPy and Pandas for analysis
- Exploratory data analysis and visualisation
- Statistics for ML, the parts you'll actually use
AI / ML
From data wrangling to deployed models.
- DPIIT-recognized
- Top 100 Innovators at IIT Delhi
- Live Projects
- Mentorship
The full AI/ML pipeline. Clean a dataset, train a model, evaluate it honestly, and put it behind an API that someone else can actually call.
Tools you'll master
PythonNumPyPandasScikit-learnTensorFlowOpenCVFastAPI
What you walk away with
A trained model deployed behind a FastAPI endpoint, with a written report.
45-day plan
Structured phases, each with a specific outcome. The final phase is always a real, shipped piece of work.
Phase 2 · Day 11–22
Core
Build and evaluate real models
- Scikit-learn: regression, classification, clustering
- Feature engineering and pre-processing
- Cross-validation and honest evaluation
- Model interpretability and bias
Phase 3 · Day 23–34
Specialisation
Deep learning + computer vision
- Neural networks with TensorFlow / Keras
- Computer vision with OpenCV
- Transfer learning and fine-tuning
- GPU-aware training basics
Phase 4 · Day 35–45
Live Project
Deployed, documented model
- Pick a real problem, define metrics
- Train, evaluate, iterate
- Wrap with FastAPI and deploy
- Final report + API demo
Apply to the AI/ML track
Send your application below. Our team will reach out within two working days with the next steps for the AI / ML track.
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