Learn AI — curated, no noise
Courses, tutorials, papers, and docs hand-picked by the TuningsFolks team. From absolute beginner to production-grade AI engineering.
⭐ Featured picks
CS224N: Natural Language Processing with Deep Learning
Stanford Online
Stanford's flagship NLP course — lecture videos, slides, and assignments freely available. Covers attention, BERT, GPT, and the math behind them.
Hugging Face NLP Course
Hugging Face
Official Transformers course — fine-tuning, pipelines, and the full Hugging Face ecosystem. Hands-on notebooks for every chapter.
Practical Deep Learning for Coders
fast.ai
Fast.ai's top-down, code-first course — start with working models, learn the theory as you need it. Covers CNNs, NLP, tabular, and diffusion models.
All resources
Amazing Digital Dentures (a failed project)
Hugging Face
A post-mortem analysis of a failed digital dentures project that serves as a learning resource about project challenges and lessons learned.
Harness, Scaffold, and the AI Agent Terms Worth Getting Right
Hugging Face
An explainer clarifying key terminology and concepts related to AI agents, harnesses, and scaffolding to help practitioners use accurate language.
Specialization Beats Scale: A Strategic Variable Most AI Procurement Decisions Overlook
Hugging Face
A strategic guide examining how specialization in AI procurement outperforms scaling approaches in organizational decision-making.
Unlocking asynchronicity in continuous batching
Hugging Face
A guide explaining how to implement asynchronous processing in continuous batching systems for improved performance.
Papers With Code — State of AI
Papers With Code
Every major ML paper with linked open-source code and live benchmark leaderboards. The fastest way to find reproducible baselines and track state-of-the-art.
LangChain: Build LLM Applications
LangChain
Official LangChain tutorials on chains, agents, RAG, and memory. Best entry point for building production-grade LLM apps in Python.
OpenAI Cookbook
OpenAI
Practical code examples for LLM patterns — embeddings, function calling, RAG, vision, batch. Fastest path from idea to working code with OpenAI APIs.
Neural Networks: Zero to Hero
YouTube / Karpathy
Andrej Karpathy builds neural nets from scratch in Python — from micrograd (100-line backprop) to a full GPT. Legendary for clarity.
Prompt Engineering Guide
DAIR.AI
Comprehensive guide to prompting: zero-shot, few-shot, chain-of-thought, ReAct, self-consistency. Maintained by DAIR.AI.
DeepLearning.AI — LLMOps Specialization
DeepLearning.AI
Andrew Ng's short course on deploying and maintaining LLMs in production. Covers CI/CD for AI, evaluation pipelines, and model drift.
Anthropic Prompt Engineering Guide
Anthropic
Anthropic's definitive guide to prompting Claude — zero-shot, system prompts, tool use, and multi-turn conversation design.