track · build
AI/ML Track
From Python fundamentals to shipping real AI/ML projects — built around the LEE arc: Learn it, Engineer it, Excel at it.
› stage/01/learnLearn
- Python for AI and data handling (NumPy, pandas)
- ML fundamentals: regression, classification, model evaluation
- GenAI & LLM fundamentals: prompt engineering, embeddings, retrieval-augmented generation (RAG)
- Working with real model APIs and open-weight models
› stage/02/engineerEngineer
You'll build and ship 6 production-style projects, not tutorials — for example:
- A resume-to-job-description matching tool using embeddings
- A RAG-based chatbot over a real document set
- An image classification model deployed behind a simple API
- A recommendation engine on real tabular data
- A fine-tuned small language model for a narrow task
- An end-to-end ML pipeline: data in, model out, served
› stage/03/excelExcel
- 3 mock interviews with recorded, actionable feedback
- Resume and LinkedIn rebuilt specifically for AI/ML Engineer and Data Scientist roles
- Portfolio review before you start applying
Choose Your Format
Self-paced learners who want a personalized schedule.
- Full curriculum
- Weekly 1:1 sessions
- Paced to you
Learners who want peer accountability on a fixed schedule.
- Full curriculum
- Structured batch sessions
- Peer projects
Learners who want full support through to an offer.
- 1:1 or Cohort format
- Full placement support
- Interview prep
Includes full placement support and interview prep.