Free AI Learning Resources: Curated by AI Engineering Lab

The big AI companies all teach their own stacks for free. This page catalogs the ten major programs, tells you what each one is actually good for, and maps it to the weeks of this program, so you always know which external course complements the week you are in.

How to use this page: this program is your spine; these resources are the cross-training. Do the Zorost week first, then dip into the mapped resource if you want a second explanation, a vendor's official voice, or a certificate to show.

Part of AI Engineering Lab · Developed by Zorost Intelligence AI Lab · zorost.com

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The ten company programs

#	Provider	Link	What it is	Best for	Pairs with weeks
1	Anthropic	anthropic.skilljar.com	Anthropic's official courses: Claude API, prompt engineering, tool use, MCP, Claude Code	The vendor voice on prompting, agents, and MCP, straight from the team that builds Claude	W6, W12, W14, W16
2	Google	grow.google/ai	Google's AI learning hub: essentials, Gemini, Vertex AI paths	Beginner-friendly AI literacy, then Google Cloud's GenAI stack	W1 to 5, W19
3	Meta	ai.meta.com/resources	Meta AI's resource hub: Llama models, research papers, tooling docs	Understanding the Llama open-weight ecosystem from its source	W8 to 10
4	NVIDIA	developer.nvidia.com/cuda	The CUDA platform docs and GPU programming resources (plus DLI courses)	What a GPU actually is, CUDA fundamentals, why VRAM math works the way it does	W8 to 9
5	Microsoft	learn.microsoft.com/training	Microsoft Learn: free structured paths for Azure, AI Foundry, Copilot	The official Azure AI Foundry training that Week 18 builds on; AZ/AI cert prep	W18
6	OpenAI	academy.openai.com	OpenAI Academy: free courses and live sessions on OpenAI tools and AI fluency	API patterns, structured outputs, and a second vendor's framing of prompt engineering	W5 to 7
7	IBM	skillsbuild.org	IBM SkillsBuild: free tech career courses with credentials	Beginners who want a structured, credentialed on-ramp; also strong on AI ethics	W1 to 3
8	AWS	skillbuilder.aws	AWS Skill Builder: the official AWS training platform, incl. Bedrock and ML paths	The official Bedrock/SageMaker training behind Week 20; AWS cert prep	W20
9	DeepLearning.AI	deeplearning.ai	Andrew Ng's course platform: short courses and specializations across GenAI, ML, agents	The conceptual depth behind this program's framework, short courses pair beautifully with hard weeks	W3 to 11, W14 to 16
10	Hugging Face	huggingface.co/learn	HF's free courses: NLP/Transformers, smol models, agents, audio, ML for games	Hands-on transformers, tokenizers, and the HF Agents course, the closest free cousin to Weeks 5 to 10	W5 to 10, W14

Honorable mention: systems thinking

Resource	Link	Why it is here
Best System Design Resources	github.com/javabuddy/best-system-design-resources	A curated index of system-design material. AI engineering is system design with probabilistic components, cost, reliability, and scale tradeoffs (Skill 2 of the Skills Map) are learned here. Pairs with W1 to 2, W13, W18 to 24.

The mapping, by phase

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flowchart LR
    subgraph SPINE["AI Engineering Lab (the spine)"]
        P1["W1 to 4 Foundations"] --> P2["W5 to 8 LLM Core"] --> P3["W9 to 11 Model Eng"] --> P4["W12 to 13 Harnesses"] --> P5["W14 to 17 Agents"] --> P6["W18 to 20 Clouds"] --> P7["W21 to 24 Databricks"]
    end
    IBM["IBM SkillsBuild · grow.google"] -.-> P1
    HF1["Hugging Face Learn · OpenAI Academy"] -.-> P2
    META["Meta AI resources · HF courses"] -.-> P3
    ANT1["Anthropic Skilljar"] -.-> P4
    ANT2["Anthropic Skilljar · HF Agents"] -.-> P5
    MSL["Microsoft Learn · AWS Skill Builder · grow.google"] -.-> P6
    DLA["DeepLearning.AI, conceptual depth throughout"] -.-> P2
    NV["NVIDIA CUDA/DLI"] -.-> P3

Rules for using external courses

1. The spine wins. If an external course conflicts with your week, finish the week first. Depth in one curriculum beats five half-finished ones.
2. Vendor courses teach vendor tools. Anthropic's prompt course is excellent, and it teaches Claude. The transfer skill (you, on a second vendor's model) is exactly what Weeks 18 to 20 drill.
3. Certificates are byproducts. If a course offers one, take it, but the artifact this program builds (your fork, your tracker, your capstone) is the credential that survives an interview.
4. Found a better free resource? Add it, see .github/CONTRIBUTING.md. Keep entries free-tier genuine, named, and mapped to a week.

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