⚒️ 9 projects with step-by-step milestones
Build your AI portfolio
Real projects that hiring managers notice. Each comes with a tech stack, milestones, interview questions you'll face, and portfolio guidance.
Beginner
3 projectsStart here — no prior ML experience needed
AI Chatbot with Memory
Build a simple chatbot that remembers the last 5 messages in the conversation using the OpenAI or Claude API. Deploy it as a web app.
PDF Summarizer
Upload any PDF and get a structured summary — key points, section breakdown, and a one-paragraph abstract — using an LLM.
AI Resume Screener
Build a tool that takes a job description and a resume, then scores how well the resume matches the role and highlights skill gaps.
Intermediate
3 projectsFor those who know Python and basic ML concepts
Production RAG Chatbot
Build a chatbot that answers questions from your own documents using RAG — chunking, embeddings, vector search, and LLM generation with source citations.
Multi-Tool AI Agent
Build an AI agent with access to tools — web search, calculator, code executor, and a knowledge base — that can reason through multi-step tasks.
End-to-End ML Pipeline
Build a full ML pipeline — data ingestion, feature engineering, model training, evaluation, and deployment — with experiment tracking.
Advanced
3 projectsProduction-grade systems that stand out in interviews
LLM Evaluation Platform
Build a platform for evaluating LLM outputs — RAGAS-style metrics, human evaluation UI, leaderboard, and automated regression testing.
Enterprise Production RAG
Build a production-grade RAG system with multi-tenancy, reranking, hybrid search, streaming responses, observability, and LLM gateway rate limiting.
Production Multi-Agent System
Build a supervisor-worker multi-agent system where a coordinator agent delegates subtasks to specialist agents (researcher, coder, writer) with shared memory.