[Updated on 2025-09-27]
Some resources that may be useful while learning data science and LLMs.
Courses
- Home | CS324 (stanford-cs324.github.io) - CS324 - Large Language Models
- Harvard CS197: AI Research Experiences - Dive into dev tools like Pytorch, and HF
- CS231n CNN for Visual Recognition - Stanford CS class
- fast.ai - Making neural nets uncool again.
- Effective MLOps with W&B - Effective MLOps: Model Development course
- Made With ML - MLOps course
Deep learning
- Differentiable neural computer - Wikipedia - memory augmented neural network architecture.
- Speech and Language Processing (stanford.edu)
- Deep learning Cheat sheet - A summary of deep learning concepts shared by Stanford researchers.
- Learn TensorFlow and deep learning, without a Ph.D.
- TensorFlow tutorials
- google-research/tuning_playbook - A playbook for maximizing the performance of DL models.
- Data Version Control · DVC - Apply version control to ML development
- MLflow - A platform for managing the end-to-end ML lifecycle
Reinforcement Learning
- Gymnasium Documentation (farama.org) - OpenAI Gym agents.
- Proximal Policy Optimization (openai.com) - PPO algorithm, for the reinforcement learning.
- Bullet Real-Time Physics Simulation - Home of Bullet and PyBullet: physics simulation for games, visual effects, robotics and reinforcement learning.
LLM
- Unsloth Fine-tuning LLMs Guide - basics and best practices of fine-tuning
- TRL – Hugging Face - Train language models with RL
- llama.cpp - LLM inference in C++
Books
- Understanding Deep Learning, by Simon J.D. Prince - Understanding Deep Learning notes.
- Hands-On ML with Scikit-Learn, Keras, and Tensorflow
- Introduction to Statistical Learning, with R
- Discrete time Markov chains (bath.ac.uk) - a course on Markov chains
- Introduction to Probability Models - Sheldon M. Ross - Introduction to probability models
Challenges
- LeetCode - Learn and prepare for technical interviews
- Advent of Code - An advent calendar of small programming puzzles for a variety of skill levels
- Roadmap (neetcode.io) - Roadmap for practicing on LeetCode
- Challenges | Inform - NASA Space Apps Challenge
AI Newsletter
- The AiEdge Newsletter - Articles about MLOps
- Blog - neptune.ai - Articles about applied ML, experiment tracking, and model registry
- Lil’Log (lilianweng.github.io) - Personal blog from an OpenAI’s researcher
- eugeneyan - Eugen’s posts related to LLM systems
- Jay Alammar - Visualizing ML and LLM concepts
Operations research
- Operational Research, MC, IST - Learn the exact algorithms used in Linear Optimization
- Real-time Scheduling Algorithms, MJC - Resources on Scheduling algorithms applied to Supply chain
- Optimization with PuLP - PuLP 2.7.0 documentation
- OR-Tools | Google Developers - A fast and portable software for combinatorial optimization
- Beer Game - Understand the effects of the bullwhip effect on Supply chain management
Software Dev
- Developer Roadmaps - roadmap.sh
- jwasham/coding-interview-university - A complete CS study plan to become a software engineer.
- GeeksForGeeks - Learn CS and practice
- FreeCodeCamp
- Corey Schafer - Youtube - Arguably the best YouTube channel for learning Python
- TheAlgorithms/Python - All Algorithms implemented in Python
- ossu/computer-science - Path to a free self-taught education in Computer Science!
- The Modern JavaScript Tutorial - Learn JavaScript
- airbnb/javascript: - JavaScript Style guide | GitHub
Extras
- Motion Canvas - Visualize Complex Ideas Programmatically
- 3b1b/manim - Animation engine for explanatory math videos (Used by 3Brown1Blue)
- Typst - A productive alternative to using Rust
- Modelling in Blender a Human Hand
Good Read!