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.

158resources
37courses
11videos
updated weekly

Built from the resources teams actually use

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How it works

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

1

Pick a track

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

2

Follow curated resources

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

3

Build & ship

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

Browse by focus

Find the right lane fast.

Start with a level, then refine by format or deep dive.

Latest drops

Fresh resources, curated for builders.

Showing 158 resources.

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Whitepaper

Chain-of-Thought Prompting Elicits Reasoning

Wei et al.

Whitepaper

Training language models to follow instructions with human feedback

Ouyang et al.

Whitepaper

Retrieval-Augmented Generation for Knowledge-Intensive NLP

Lewis et al.

Whitepaper

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

Brown et al.

Whitepaper

BERT: Pre-training of Deep Bidirectional Transformers

Devlin et al.

Whitepaper

Training Compute-Optimal Large Language Models

Hoffmann et al.

Article

Machine Learning Interviews

Ali Rezadirad

Article

How to Become a Machine Learning Engineer

IEEE BLP

Article

RAG Evaluation Basics

Ragas

Article

Google Gemini Announcement

Google

Article

Announcing Mistral 7B

Mistral

Article

Introducing Llama 2

Meta AI

Article

Introducing Amazon Bedrock

AWS

Article

Introducing Claude

Anthropic

Article

Introducing GPT-4

OpenAI

Article

The NLP Course is becoming the LLM Course

Hugging Face

Article

Transformers: The Model Behind the Revolution

Hugging Face

Article

Function calling and other API updates

OpenAI

Article

The Illustrated GPT-2

Jay Alammar

Article

Introducing text and code embeddings

OpenAI

Article

What is Retrieval-Augmented Generation (RAG)?

Cohere

Video

Google ML Crash Course Overview

Google Developers

Video

Hugging Face Course Intro

Hugging Face

Video

Stanford CS224N Lecture Playlist

Stanford

Video

Stanford CS230 Lecture Playlist

Stanford

Video

Stanford CS231n Lecture Playlist

Stanford

Video

Stanford CS230 Lecture 1

Stanford Online

Video

MIT 6.S191 Lecture 1 (2025)

MIT DeepLearning

Video

Let’s build GPT from scratch

Andrej Karpathy

Video

OpenAI DevDay: Opening Keynote

OpenAI

Open Source

Chroma

Chroma

Open Source

Milvus

Milvus

Open Source

Weaviate

Weaviate

Open Source

Qdrant

Qdrant

Open Source

Whisper

OpenAI

Open Source

Instructor

Instructor

Open Source

Guidance

Microsoft

Open Source

LiteLLM

BerriAI

Open Source

CrewAI

CrewAI

Open Source

AutoGen

Microsoft

Open Source

DSPy

Stanford NLP

Open Source

Ragas

Ragas

Open Source

LM Evaluation Harness

EleutherAI

Open Source

OpenAI Evals

OpenAI

Open Source

Text Generation Inference

Hugging Face

Open Source

llama.cpp

ggerganov

FAQ

Good to know

Is it free?

Yes. Every resource in the Learn AI hub is free to access.

Who is this for?

Developers, engineers, and builders who want a curated path into modern AI and ML — not a random list.

Do I need an account?

No account is needed to browse. Create a free DevFound account to contribute resources and save your progress.

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