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YouTube - Channels and Videos Worth Your Time

A filtered list of YouTube content for learning cloud and AI/ML. No algorithmic slop, no engagement-bait thumbnails - just channels and individual videos that actually teach.

Curated by Patrick Wiloak. If you find dead links or want to suggest additions, see CONTRIBUTING.md.

How to use this page

YouTube is the single best free resource for learning cloud and AI - if you can find the signal in the noise. This page is the signal.

  • Channels are sorted by what they're best for, not subscriber count.
  • Single-video deep dives are linked when one video is worth more than a whole playlist elsewhere.
  • I won't link a video unless it's still accurate today. Cloud content rots fast.

If you want vendor-specific exam content, that lives in the Study Hub. This page is for learning the why and how, not memorizing exam objectives.

Start here: my channel

@patrickwiloak - my channel.

Cloud certification strategy, Claude Code workflows, agent architecture, and "what I learned passing 16 cloud certs while working at AWS." Practical, no fluff.

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Cloud Computing - Best Channels

Foundations and certifications

Stephane Maarek - Best for: AWS certifications (CCP, SAA, DVA, SAP, Specialty) - Why: Tight, accurate, exam-aligned. The most-recommended AWS course author for a reason. - Use when: You have an AWS exam date.

Adrian Cantrill - Best for: AWS deep-dive understanding (SAA, SAP, Networking, Security) - Why: Goes deeper than Maarek. Architecture-first, not just exam-first. Free YouTube content + paid courses. - Use when: You want to understand AWS at the architecture level, not just pass.

Tech with Nana - Best for: DevOps fundamentals (Kubernetes, Docker, CI/CD, Terraform) - Why: Best beginner-friendly DevOps explanations on YouTube. The Kubernetes crash course alone is worth the visit. - Use when: You're new to DevOps tooling and need clear mental models.

freeCodeCamp.org - Best for: Long-form (3-15 hour) full courses on every cloud topic - Why: Free, comprehensive, frequently refreshed. Their AWS Certified Cloud Practitioner and Terraform courses are classics. - Use when: You want a full course in one sitting (or weekend).

Specific cloud providers

John Savill's Technical Training - Best for: Microsoft Azure (AZ-104, AZ-305, AZ-500, AZ-700, AZ-900) - Why: Ex-MSFT field engineer. The single best Azure cert resource on YouTube. His exam cram videos are a rite of passage. - Use when: You're prepping for any Azure exam.

Google Cloud Tech - Best for: Official GCP service deep dives, "Cloud OnAir" sessions - Why: GCP's own product teams explaining GCP. Higher signal than most vendor channels. - Use when: You want canonical GCP content from the source.

AWS Events - Best for: re:Invent talks, deep dives by AWS engineers - Why: The 300/400-level re:Invent talks are graduate-level cloud architecture content. Free. - Use when: You want senior-level architecture thinking, not basics.

Kubernetes and containers

That DevOps Guy (Marcel Dempers) - Best for: Hands-on Kubernetes, GitOps, observability - Why: Real implementations, not slide decks. Production-grade patterns. - Use when: You can deploy a pod but don't yet know how to run K8s in production.

KubeSimplify - Best for: Kubernetes fundamentals, KCNA/CKA prep - Why: Beginner to intermediate K8s without the noise. - Use when: You're starting Kubernetes and want a guided path.

Networking

NetworkChuck - Best for: Networking fundamentals, CCNA, hands-on home lab content - Why: Energetic, practical, gets people excited about networking - a rare skill. - Use when: You're new to networking or studying CCNA / Network+.

Practical Networking - Best for: TCP/IP, OSI, routing fundamentals taught rigorously - Why: When NetworkChuck is too fast or too hype, this is your channel. Calm, accurate, foundational. - Use when: You want to actually understand how the internet works.

Security

John Hammond - Best for: Offensive security, malware analysis, CTF walkthroughs - Why: Real-world security content, not vendor marketing. - Use when: You're going beyond defensive security into red-team territory.

IppSec - Best for: HackTheBox walkthroughs, OSCP-style enumeration - Why: The standard for pentesting walkthroughs. - Use when: You're working through OSCP, HTB, or learning offensive security.

AI / Machine Learning - Best Channels

Foundations

3Blue1Brown - Best for: The math behind machine learning and neural networks - Why: The "Neural Networks" series is the gold standard. If you've seen it, you understand backprop. If you haven't, watch it. - Use when: Equations are blocking your understanding and you need geometric intuition.

Andrej Karpathy - Best for: Building ML/LLMs from scratch, in Python, with no abstractions - Why: Ex-Tesla AI / OpenAI co-founder. His "Neural Networks: Zero to Hero" series builds GPT from scratch in a Jupyter notebook. There is nothing better. - Use when: You want to build a transformer with your own hands.

StatQuest with Josh Starmer - Best for: Classical ML algorithms explained step by step - Why: Random forests, SVMs, PCA, gradient boosting - all clearly explained. "BAM!" - Use when: You're getting into a classical ML algorithm and need it broken down.

Modern AI / LLMs

Yannic Kilcher - Best for: Paper walkthroughs of frontier AI research - Why: Reads the paper with you. Best "research-level but accessible" coverage of AI. - Use when: A new paper drops (GPT-4, Claude, DeepSeek, etc.) and you want a deeper look.

Two Minute Papers - Best for: Frontier ML/CV/graphics research, accessible - Why: Two Minutes โ‰  Two minutes, but each video covers one paper, well. - Use when: You want to keep up with what's happening in research without reading every paper.

AI Explained - Best for: Frontier model news, evaluation, capability analysis - Why: Calm, well-sourced takes on what new models can actually do. - Use when: A new frontier model drops and you want signal, not hype.

Sam Witteveen - Best for: Hands-on LLM tutorials (LangChain, LlamaIndex, agents, RAG) - Why: Builder-focused LLM content. Updated frequently as the ecosystem changes. - Use when: You're building with LLMs and need working code.

Anthropic - Best for: Claude, Constitutional AI, alignment research - Why: Source-of-truth content about Claude. Great agent-building demos. - Use when: You're building with Claude or want to understand the model's design.

Practical ML engineering

Aleksa Gordiฤ‡ - The AI Epiphany - Best for: Paper walkthroughs with a code-and-math focus - Why: Goes deeper than Yannic, more code-heavy. Great for transformer internals. - Use when: You want to actually implement what's in a paper.

Umar Jamil - Best for: From-scratch implementations of transformers, LLaMA, Mistral, RAG, fine-tuning - Why: Multi-hour walkthroughs that build modern LLM components from PyTorch up. - Use when: You want to deeply understand how a specific model works internally.

Single-Video Deep Dives

These are individual videos that punch above their weight. If you only have an hour, watch one of these.

Cloud

AI / ML

General CS / engineering

Channels to be cautious of

I'm not naming names, but be skeptical of:

  • Cert farms - channels that pump out new "AWS Cert Pass in 2 Weeks!" videos with engagement-bait thumbnails. Often outdated, sometimes wrong.
  • AI hype channels - daily "GPT-X is here and it's GAME OVER" content. Burns your time, teaches nothing.
  • AI-narrated faceless channels - if the voice is synthetic and the script reads like a Wikipedia summary, it probably is one. Quality is hit-or-miss; sources usually missing.

Heuristic: if the thumbnail has a shocked face and red arrows, the actual content is probably thin.

Recommended watch order for total beginners

If you've never touched cloud and never touched ML, here's a 10-hour starter sequence:

  1. NetworkChuck - "What is the cloud?" (10 min) - frame the basics
  2. freeCodeCamp - "AWS Cloud Practitioner full course" (4 hours, watch at 1.5x) - basic AWS literacy
  3. Tech with Nana - "Kubernetes Crash Course" (1 hour) - containers and orchestration fundamentals
  4. 3Blue1Brown - Neural Networks series ep. 1-4 (1 hour) - what an NN actually is
  5. Andrej Karpathy - "Intro to Large Language Models" (1 hour) - what LLMs actually are
  6. AI Explained - any recent capability deep-dive (15 min) - what frontier AI can do today

After this, you can navigate the rest of YouTube without getting lost. Come back here when you want to go deeper on a specific topic.

Companion docs

Suggest an addition

Found a channel or video that should be here? Open a PR or issue. Criteria: - Still accurate today (cloud rots fast) - Teaches you something, not just hype - Not a sponsorship-disguised-as-content video - Bonus: small or undiscovered creators teaching well

Contributing Guide