AI Developer

Ship working AI applications and explain how they are built.

7 milestones • Python and ML basics → LLM apps → an AI project → portfolio.

1. 1

   Python foundations

   Write clean Python: functions, data structures, files and APIs.

   Data science & AI track
2. 2

   Machine learning basics

   Understand supervised learning, evaluation and common models.

   Data science sheet
3. 3

   Build with LLM APIs

   Call an LLM API, design prompts and handle structured output.

   Live workshops
4. 4

   Ship an AI project

   Deploy an AI app or automation that solves a real problem.

   AI for Your Career challenge
5. 5

   Problem-solving practice

   Build interview-ready problem-solving with the DSA sheet.

   DSA sheet
6. 6

   Get a mentor review

   Walk a mentor through your project and get feedback.

   Find a mentor
7. 7

   Interview practice

   Prepare for technical and project-deep-dive interviews.

   Interview prep