AWSListed
AWS Training
AWS Generative AI Learning Plan
For: Engineers at AWS-stack companies
Intermediate · ~20-40 hours (modular) · Free
AWS Generative AI Learning PlanvsNeural Networks: Zero to Hero (Andrej Karpathy)
Side-by-side comparison on level, duration, pricing, instructor, tier. Editor verdict on which course wins for which buyer.
AWS
AWS Training
AWS Generative AI Learning Plan
AWS's free learning path for engineers building on Bedrock. Covers the AWS-specific patterns (Bedrock, SageMaker, Knowledge Bases for RAG, Bedrock Agents) plus general LLM/RAG concepts. Free, vendor-locked, useful only if your stack is AWS. The AI Practitioner cert ($100) and ML Engineer Associate ($150) build on this learning plan; pair with our /learn/certifications page for the cert side.
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YouTube
Neural Networks: Zero to Hero (Andrej Karpathy)
The single most-recommended free resource in modern AI education. Karpathy builds a working autograd engine, then a character-level language model, then a tokenizer, then a working GPT — all from scratch in PyTorch, explaining every line. The 'Let's build GPT' and 'Let's build the GPT Tokenizer' lectures specifically have become canonical references — every senior AI engineer has watched them. The catch: it's 25 hours of dense math-and-code video. You won't follow if you can't keep up with Python + linear algebra. But if you can, no paid course delivers comparable depth.
Side-by-side
| Dimension | AWS Generative AI Learning Plan | Neural Networks: Zero to Hero (Andrej Karpathy) |
|---|---|---|
| Provider | AWS Training | YouTube |
| Editorial tier | Listed | Hands-on reviewed |
| Level | Intermediate | Advanced |
| Format | self paced | video |
| Duration | ~20-40 hours (modular) | ~25 hours (11 lectures) |
| Pricing | Free | Free |
| Instructor | AWS Training & Certification — AWS | Andrej Karpathy — Co-founder OpenAI; former Director of AI at Tesla |
| Rating | No public rating | No public rating |
| Topics | llm fundamentals, fine tuning, rag systems | llm fundamentals, fine tuning, ai engineering |
| Last verified | 2026-05-24 | 2026-05-23 |
Pros & cons
AWS Generative AI Learning Plan
Pros
- +Free, comprehensive AWS-stack curriculum
- +Direct prep for AWS AI Practitioner + ML Engineer Associate certs
- +AWS Bedrock content is the deepest available for that platform
Cons
- −AWS-locked — patterns don't transfer to GCP / Azure
- −Some labs require small AWS spend ($5-20)
- −Tier 3 because we list rather than personally vet every module
Neural Networks: Zero to Hero (Andrej Karpathy)
Pros
- +By a co-founder of OpenAI — no higher-authority instructor exists
- +Free, on YouTube, with companion GitHub code
- +The "Let's build GPT from scratch" lecture is the single most-cited free resource in AI education
Cons
- −25-hour commitment of dense material — you have to actually do the exercises
- −Pre-reqs are real: comfortable Python + undergrad linear algebra
- −No certificate, no community — pure self-direction
Which course is for whom?
AWS Generative AI Learning Plan
Best for
- · Engineers at AWS-stack companies
- · Anyone preparing for AWS AI certs
Not ideal for
- · Non-AWS teams — wrong vendor focus
Neural Networks: Zero to Hero (Andrej Karpathy)
Best for
- · Engineers who plan to train, fine-tune, or research LLMs at depth
- · Anyone tired of "wrapper" courses who wants to understand transformers from first principles
Not ideal for
- · Casual learners — the dropout rate on the lecture series is high for a reason
- · Anyone wanting application patterns (LangChain, prompt engineering) — wrong course
Editor's short verdict
Take Neural Networks: Zero to Hero (Andrej Karpathy) first if you're new to the topic; once you have the basics, AWS Generative AI Learning Plan is the natural next step. They're complementary in a learning path, not directly competing.
▶Hands-on reviewedEditor's pick
YouTube
Neural Networks: Zero to Hero (Andrej Karpathy)
For: Engineers who plan to train, fine-tune, or research LLMs at depth
Advanced · ~25 hours (11 lectures) · Free
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