curriculum

Shared an AI introductory course of 12 weeks and 24 lessons, covering from symbolism to neural networks, CNN, RNN, GAN, genetic algorithms, and multi-agent systems, with PyTorch and TensorFlow dual-version notebooks, suitable for systematic learning of AI knowledge.

Discussing the high cost of EE/CS education, encouraging a search for an open-source electrical and electronic engineering course repository on GitHub, believing that the revolution in higher education will develop rapidly from this.

A tweet promoting a curated learning path covering key AI engineering concepts, claiming a personal BSc-equivalent education in 3 weeks.

A GitHub repository curating courses from top universities (Harvard, MIT, Stanford, etc.) into a structured computer science degree, with prerequisites and workload details, offering a free learning roadmap without a diploma.

A curated list of open-source computer science courses on GitHub, open-source-cs, featuring free public courses from top universities like MIT and Stanford, arranged according to the undergraduate curriculum. Already with 20k+ Stars, it's ideal for self-learners seeking systematic study.

A full-stack AI engineering learning path from zero to mastery, containing 503 lessons covering from math basics to autonomous agent clusters, with full Chinese translation and a dedicated website.

The University of Michigan has made its entire robotics degree curriculum freely available on GitHub, including lecture videos, textbooks, and assignments, starting with practical linear algebra for robotics.

Harvard has open-sourced its entire ML Systems curriculum, but the author argues it alone won't get data scientists high-paying AI roles.

This paper proposes a system that combines a prerequisite knowledge graph with a PPO-based policy to structure Socratic tutoring with LLMs, showing improved student mastery and efficiency over heuristic and frontier model baselines.

A free, open-source AI engineering curriculum covering 20 phases from linear algebra to autonomous agent swarms, with hands-on building in Python, TypeScript, Rust, and Julia. All materials are reusable and connectable to Claude Code or Cursor.

DanKornas introduces an open-source AI Infrastructure Engineer Learning Path, a structured 10-module curriculum covering foundations to LLM infrastructure with hands-on labs and projects.

A structured 19-phase AI/ML learning curriculum covering topics from setup and math to capstone projects, created by @ghumare64.

A hands-on PyTorch curriculum that teaches LLM training from transformer basics through fine-tuning and alignment, including RLHF and GRPO.

Recommends an open-source AI engineering learning course, containing 20 stages and 503 lessons, covering from math fundamentals to production deployment, including Python and other languages, aiming to build a complete AI engineering system from scratch.

Microsoft released a free, open-source AI degree curriculum on GitHub covering neural networks, deep learning, NLP, transformers, LLMs, generative AI, and more.

A comprehensive 500-hour learning path for AI Infrastructure Engineering, covering Docker, Kubernetes, MLOps, LLM infrastructure, and more through hands-on projects and labs.

A curated video-guided curriculum and comprehensive list of resources for learning ML systems and LLM infrastructure, including papers, courses, and tutorials.

A free, open-source AI engineering curriculum on GitHub with 435 lessons, teaching from raw math to production deployment across multiple languages.

Recommends an open-source GitHub repo called ai-engineering-from-scratch, containing 435 lessons across 20 stages, systematically covering a complete learning path for AI engineering from math foundations to Agents.

A free, open-source curriculum that teaches AI engineering from first principles, building algorithms from raw math before using frameworks. It consists of 435 lessons across 20 phases, supporting Python, TypeScript, Rust, and Julia.