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AI Learning Hub · 158 resources

Build production-grade AI, faster.

A focused library for builders — LLM architecture, agents, evaluation, and deployment, sequenced into tracks instead of a firehose of links.

Browse 158 resources

158resources

37courses

11videos

updated weekly

Track · Agentic Workflows live

Foundations Architecture Agents Production

ReAct: Reasoning + ActingPaper

OpenAI Guide: Function CallingTutorial

ToolformerPaper

vLLM DocumentationTutorial

Track progress0%

Built from the resources teams actually use

Inside a track

Four lanes. Each one a sequence, not a pile.

Every track is an ordered path through the best free resources for one outcome — so you always know what to read next.

1 OpenAI Guide: Function Calling OpenAI Tutorial

2 vLLM Documentation vLLM Tutorial

3 NVIDIA NeMo Documentation NVIDIA Tutorial

4 Gemini API Quickstart Google Tutorial

5 PyTorch Tutorials PyTorch Tutorial

1 Llama 2: Open Foundation and Fine-Tuned Chat Models Touvron et al. Whitepaper

2 PaLM: Scaling Language Modeling with Pathways Chowdhery et al. Whitepaper

3 Language Models are Few-Shot Learners (GPT-3) Brown et al. Whitepaper

4 BERT: Pre-training of Deep Bidirectional Transformers Devlin et al. Whitepaper

5 Training Compute-Optimal Large Language Models Hoffmann et al. Whitepaper

1 Toolformer: Language Models Can Teach Themselves Schick et al. Whitepaper

2 ReAct: Synergizing Reasoning and Acting Yao et al. Whitepaper

3 Function calling and other API updates OpenAI Article

4 CrewAI CrewAI Open Source

5 AutoGen Microsoft Open Source

1 Introducing Amazon Bedrock AWS Article

2 LiteLLM BerriAI Open Source

3 OpenAI Evals OpenAI Open Source

4 Text Generation Inference Hugging Face Open Source

5 vLLM vLLM Open Source

How it works

From “where do I start?” to shipping — in three steps

Pick a track

Start from a level or focus area — foundations, architecture, agents, evaluation.

Follow curated resources

Hand-picked articles, videos, courses, and tools that builders actually use.

Build & ship

Apply what you learn to real projects, then go find the role to match.

Latest drops

Fresh resources, curated for builders.

Showing 158 resources · updated weekly

View all

Whitepaper

Llama 2: Open Foundation and Fine-Tuned Chat Models

Touvron et al.

Build production-grade AI, faster.

Four lanes. Each one a sequence, not a pile.

From “where do I start?” to shipping — in three steps

Pick a track

Follow curated resources

Build & ship

Find the right lane fast.

Fresh resources, curated for builders.

Llama 2: Open Foundation and Fine-Tuned Chat Models

PaLM: Scaling Language Modeling with Pathways

Toolformer: Language Models Can Teach Themselves

ReAct: Synergizing Reasoning and Acting

Chain-of-Thought Prompting Elicits Reasoning

Training language models to follow instructions with human feedback

Retrieval-Augmented Generation for Knowledge-Intensive NLP

Language Models are Few-Shot Learners (GPT-3)

BERT: Pre-training of Deep Bidirectional Transformers

Training Compute-Optimal Large Language Models

Machine Learning Interviews

How to Become a Machine Learning Engineer

RAG Evaluation Basics

Google Gemini Announcement

Announcing Mistral 7B

Introducing Llama 2

Introducing Amazon Bedrock

Introducing Claude

Introducing GPT-4

The NLP Course is becoming the LLM Course

Transformers: The Model Behind the Revolution

Function calling and other API updates

The Illustrated GPT-2

Introducing text and code embeddings

What is Retrieval-Augmented Generation (RAG)?

Google ML Crash Course Overview

Hugging Face Course Intro

Stanford CS224N Lecture Playlist

Stanford CS230 Lecture Playlist

Stanford CS231n Lecture Playlist

Stanford CS230 Lecture 1

MIT 6.S191 Lecture 1 (2025)

Let’s build GPT from scratch

OpenAI DevDay: Opening Keynote

Chroma

Milvus

Weaviate

Qdrant

Whisper

Instructor

Guidance

LiteLLM

CrewAI

AutoGen

DSPy

Ragas

LM Evaluation Harness

OpenAI Evals

Text Generation Inference

llama.cpp

Good to know

Start building production-grade AI — free