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AI & ML — Beginner → Pro (Interactive Roadmap)

Triage, learn, practice, and show — a step-by-step single-page guide with interactive trackers and mini projects.

Roadmap overview

1

Foundations

Python, math (linear algebra, calculus, probability), git, Linux basics.

2

Core ML

Supervised learning, regression, classification, validation, scikit-learn, feature engineering.

3

Deep Learning

Neural networks, PyTorch/TensorFlow, CNNs, RNNs, transformers basics.

4

Production & Advanced

Model deployment, MLOps, interpretability, scaling, state-of-the-art papers.

Weekly plan generator

Pick your hours per week and target weeks per level — the planner will generate a suggested schedule.

Mini projects (practice)

  1. Data cleaning & EDA: Titanic or similar — produce a report and charts.
  2. Classic ML: House price regression, classification with scikit-learn.
  3. Deep learning: Image classifier (transfer learning) with PyTorch.
  4. NLP: Sentiment analysis with transformers and fine-tuning.
  5. End-to-end: Deploy a simple model with FastAPI and Docker.

Code playground (HTML/JS)

Output: