🚀 ModelX-ML30 Bootcamp
Welcome to the ModelX-ML30 Bootcamp, a comprehensive 30-week journey through the world of Machine Learning, AI, and real-world systems design.
This bootcamp is designed for aspiring ML engineers, data scientists, and builders who want to master the foundations and scale toward production-grade systems.
Youtube videos : www.youtube.com/@DebjyotiPaul-z2s
Over 30 weeks, you'll cover topics ranging from core ML theory to cutting-edge deep learning, recommendation systems, and generative models.
Each week includes conceptual lectures, Colab-based assignments, and industry-aligned projects.
| Week | Topic | Highlights |
|---|---|---|
| 1 | Classical Supervised ML Theory | MLE, MAP, Linear & Logistic Regression |
| 2 | Recommendation Systems - Part 1 | Popularity-based, User-User & Item-Item CF |
| 3 | Recommendation Systems - Part 2 | SVD, Latent Representations, Cold Start |
| ... | ... | ... |
| 30 | Capstone Project Showcase | Build, explain, and deploy a full-stack ML project |
🔗 All weekly content links below will be updated as we progress.
ModelX-ML30-Bootcamp/
├── Week1-Classical-ML/
│ ├── lecture_notes.md
│ ├── assignment.ipynb
│ └── resources/
├── Week2-Recommender-Systems-Part1/
│ ├── Week2-Part1-Readme.md
│ └── notebook_colab.ipynb
├── ...
└── README.md