Jira For Scrum Masters -> apetech.me/scrumMasters.html

this guy literally put a full AI engineering curriculum on GitHub and made it 100% FREE 🤯 435 lessons. 20 phases. 320 hours. The rule that makes this curriculum completely different: Every algorithm gets implemented from raw math before a single framework gets imported. You build the backprop. You build the tokenizer. You build the attention mechanism. By the time you use PyTorch, it’s just a shortcut for something you already know how to code from scratch. It spans four languages: → Python for ML pipelines → TypeScript for agent tooling → Rust for performance-critical components → Julia for numerical computation And the best part? Every single lesson ships something you can actually use. You walk away with fully deployable prompts, SKILL. md files, agents, and MCP servers. The curriculum scales from foundational math all the way up to autonomous agent swarms and production infrastructure. Free, open-source, and MIT licensed. repo in 🧵↓

20 GitHub repositories that will give you superpowers:↓

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Forget the noise. If you want a solid foundation in AI, this 9-part @Stanford series is still one the gold standards. Just the core fundamentals explained by the people who teach this for a living. Lecture 1 - Transformer: → youtube.com/watch?v=Q86qzJ1K… Lecture 2 - Transformer-Based Models & Tricks: → youtube.com/watch?si=PxU67AL… Lecture 3 - Transformers & Large Language Models: → youtube.com/watch?v=VlA_jt_3… Lecture 4 - LLM Training: → youtube.com/watch?v=VlA_jt_3… Lecture 5 - LLM tuning: → youtube.com/watch?v=PmW_TMQ3… Lecture 6 - LLM Reasoning: → youtube.com/watch?v=k5Fh-UgT… Lecture 7 - Agentic LLMs: → youtube.com/watch?v=h-7S6HNq… Lecture 8 - LLM Evaluation: → youtube.com/watch?v=8fNP4N46… Lecture 9 - Recap & Current Trends: → youtube.com/watch?v=Q86qzJ1K… Master the basics, and the rest gets easy.

A Google Cloud engineer just showed how to build a full app with Claude from scratch he spent 26 minutes showing exactly what one person with Claude can do, completely free worth more than any $500 vibe-coding course here's what he covers: > raw idea to deployed app in a single session > using Claude as the entire engineering team > the exact workflow they use at Google > no big team, no prior experience needed the people who figure out what Claude can actually do are building things everyone else thinks requires a team that's exactly why I put together a guide on Claude features most people have no idea exist the guide is in the article below

Anthropic pays $750,000 a year for engineers who know how to build LLMs from scratch. Stanford just released the exact lecture that teaches it - 1 hour 44 minutes, free, straight from CS229. Bookmark and watch it this weekend. It'll teach you more about how ChatGPT & Claude actually work than most people at top AI companies learn in their entire careers.

Anthropic just showed a 27-minute workshop on how to actually do prompts for Claude. Taught by the people who built it. Free. No registration. No paywall. I've seen $300 courses that don't cover what they teach in the first 8 minutes. Watch it and bookmark it now.

🚨 Anthropic just showed a 28-minute workshop on how to actually do prompts for Claude. Taught by the people who built it. Free to watch. No signup. Pure gold I've seen $300 courses that don't cover what they teach in the first 8 minutes. Watch it and bookmark it now.

Instead of watching a 2-hour movie, watch this video break down how AI is about to reshape jobs, money, and power over the next decade.

Best YouTube Channels To Learn in 2026 1. Cybersecurity – John Hammond 2. Artificial Intelligence – Andrej Karpathy 3. AI Research Breakdown – Yannic Kilcher 4. Web Development – The Net Ninja 5. Python Programming – Corey Schafer 6. DevOps – TechWorld with Nana 7. Cloud Computing – AWS re:Invent 8. Data Analytics – Luke Barousse 9. System Design – Gaurav Sen 10. Databases – Hussein Nasser 11. Low-Level Programming – The Cherno 12. Linux – Learn Linux TV 13. Networking – David Bombal 14. Math for ML – 3Blue1Brown

After 6 months of using NotebookLM, I can say it's the research tool that has revolutionized my workflow the most. But only because I learned these 10 prompts. Here's the complete system that turns 200 pages into clear answers in under an hour:

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BREAKING: Claude can now build your entire personal wealth operating system better than most financial coaches. Here are 7 prompts to automate clarity, growth, and calm:

Harvard made its Senior Engineer roadmap available to the public at no cost. Stop paying for $2,000 bootcamps. Prof. Vijay Janapa Reddi just put the entire ML Systems (CS249r) curriculum on GitHub. If you master these 6 pillars, you're ahead of 99% of the field: 🏛️ Architecture 🚿 Data Pipelines 🚢 Production 🛠️ MLOps 🔋 Edge AI 🔒 Privacy This is the "Black Box" of Big Tech infrastructure, open-sourced. Read. Learn. Bookmark.

Anthropic just launched the Claude Architect Certification! You’ll have to complete 60 multiple-choice questions across five competency areas in a single session. No external resources or breaks. Here’s how I’m planning to prepare for it (steal my roadmap): Week 1 Complete the recommended courses: - Building with the Claude API - Introduction to Model Context Protocol - Claude Code in Action - Claude 101 Week 2 Build real projects with: - Claude Code - Agent SDK - Anthropic API - MCP Week 3 Get familiar with the exam structure and guide: - Go through the six exam scenarios - Get familiar with the five competency areas / domains - Learn the skills needed for each task assessment Week 4 Do the preparation exercises from the exam guide: - Build a Multi-Tool Agent with Escalation Logic - Configure Claude Code for a Team Development Workflow - Build a Structured Data Extraction Pipeline - Design and Debug a Multi-Agent Research Pipeline Week 5 - Take the practice exam - Aim for a score greater than 850 / 1000 Week 6 - Take the real exam - Only one attempt allowed NOTES: - At this point the certification is exclusive for Anthropic Partners and early access is free for first 5,000 partner company employees. - Your mileage may vary depending on your skill level. E.g. It may take 2 weeks for some but 10 weeks for others. If you are eligible, register here → lnkd.in/eEYwUGV5

Probably one of the best "from scratch" AI series out there.

Google just dropped a FREE AI Agents course. And almost no one is talking about it. 10 code samples, whitepapers, hands-on projects... all in one place. Here’s the full breakdown (5 days): Day 1: Foundations of AI Agents Learn how agents actually work: • Architecture • Capabilities • How they differ from LLMs → Build systems that can perceive, plan, act Whitepaper: lnkd.in/grYivvCW Code: lnkd.in/gcDruAx7 Day 2: Tools & MCP (Model Context Protocol) Agents don’t work alone. Learn: • Tool usage & APIs • MCP architecture • Human-in-the-loop workflows Whitepaper: lnkd.in/gnU9yqqW Code: lnkd.in/g5ZQHGzg Day 3: Context Engineering (Memory) This is where agents become powerful. • Sessions → short-term memory • Persistent memory → long-term learning Whitepaper: lnkd.in/g9WztfuP Code: lnkd.in/g4mQEtPE Day 4: Agent Quality Production-ready systems need reliability. Learn: • Logs, traces, metrics • Evaluation frameworks • LLM-as-a-judge Whitepaper: lnkd.in/g-SAMSpV Code: lnkd.in/gJxMN46g Day 5: From Prototype → Production Where most people fail. • Deployment strategies • Scaling agents • Agent-to-Agent communication • Vertex AI ecosystem Whitepaper: lnkd.in/gnUAscjM Code: lnkd.in/gnikixYA This is basically a complete roadmap to building AI agents in 2026. And it’s 100% free. Save this. You’ll need it later 💾 Like 👍 • Repost ♻️ Follow for no-BS AI insights 🚀

A senior Google engineer just dropped a 421-page doc called Agentic Design Patterns. Every chapter is code-backed and covers the frontier of AI systems: → Prompt chaining, routing, memory → MCP & multi-agent coordination → Guardrails, reasoning, planning This isn’t a blog post. It’s a curriculum. And it’s free.