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AI/ML Mastery Program

A free curriculum from first-year programming through production AI systems: practice notebooks with solutions, end-to-end projects, and in-depth guides. Written while completing the Professional Certificate in AI & Machine Learning — Simplilearn with E&ICT Academy, IIT Kanpur.

  • Practice notebooks & solutions

    Paired exercise and answer notebooks for every course topic. Open in Colab — nothing to install.

    Start practicing

  • Projects & capstones

    Full projects (marketing, sales, loans, RAG, Netflix studio, autonomous driving, and more) plus a second architecture for each one.

    Open projects

  • Guides

    Deep notes with diagrams, math, code and interview questions — CS, Python, math, ML, deep learning, LLMs, agents, MLOps.

    Browse guides

  • Support the project

    The site stays free. If it helped, a contribution via Razorpay (UPI, cards, net banking) funds the next chapter.

    Support

How to use this site

  1. Practice a topic in Colab, then check the matching solutions notebook.
  2. Read the guide when you want the why, the math and the failure modes.
  3. Build a project when you can explain the topic out loud.
flowchart LR
    A[Practice] --> B[Guide] --> C[Project] --> D[Interview Q and A]

Practice

Section What you get
Notebooks & Solutions Graded exercises + worked answers, course by course
Guided Demos Short walkthroughs of one technique at a time
Course Projects End-to-end notebooks with write-ups
Projects, Version 2 Same problems, different architectures
Interview Q&A Topic question banks with model answers

Guides

  • CS Foundations — computers, data structures, algorithms. Open
  • Python — fundamentals through CPython internals. Open
  • Mathematics — linear algebra, calculus, probability for ML. Open
  • Data Engineering — NumPy, Pandas, cleaning, features. Open
  • Classical ML — regression, trees, boosting, SVMs. Open
  • ML Theory — validation, metrics, tuning. Open
  • Deep Learning — nets, backprop, optimizers. Open
  • Computer Vision — CNNs, detection, ViTs. Open
  • NLP — embeddings, RNNs, attention. Open
  • Transformers & LLMs — GPT/BERT, fine-tuning, LoRA. Open
  • Generative AI — RAG, vector DBs, diffusion. Open
  • AI Agents — tools, planning, multi-agent. Open
  • MLOps — Docker, serving, monitoring. Open
  • AI System Design — recs, RAG, fraud systems. Open
  • Projects & Interview — tiers 1–8 and staff-level banks. Open