INSTEAD OF WATCHING NETFLIX TONIGHT. Spend 1 hour with this. Claude AI FULL COURSE that teaches you how to BUILD and AUTOMATE anything. The people who watch this tonight will wake up tomorrow with a new skill. Watch it and bookmark it now.

How to build your first AI agent (Full guide)

🚨BREAKING: Andrej Karpathy just killed coding forever. He calls it "VIBE CODING" Describe what you want in English, and AI builds the entire app. No syntax. No debugging. No $150K CS degree. Here are 9 Claude prompts that turn anyone into a software engineer:

Cancel weekend plans. You need to: • Learn Claude Code • Learn Codex • Build 1–2 workflows in Cowork • Set up Perplexity Computer & Finance • Optimize Cowork (plugins skills) • Set up OpenClaw • Test Google AI tools (Nano Banana 2, NotebookLM, etc.) • Try basic agentic tools (Manus) • Use AI to create a business plan • Build an AI second brain (Notion) • Try Notion Agents • Learn automation (MCPs, Zapier, n8n) • Learn prompt engineering • Read AI research/articles • Explore robotics

CLAUDE FULL COURSE 4 HOURS This is the most detailed Claude guide I’ve seen online. Bookmark this before you forget. 4 hours. Build tools. Automate work. Learn how people build bots and systems. Claude → Tools → Automation → Products → Money

Cancel weekend plans. You need to: • Learn Claude Code • Build 1–2 workflows in Cowork • Set up Perplexity Computer & Finance • Optimize Cowork (plugins skills) • Set up OpenClaw • Test Google AI tools (Nano Banana 2, NotebookLM, etc.) • Try basic agentic tools (Manus) • Use AI to create a business plan • Build an AI second brain (Notion) • Try Notion Agents • Learn automation (MCPs, Zapier, n8n) • Learn prompt engineering • Read AI articles • Explore robotics

🚨 BREAKING: HuggingFace just dropped their complete AI engineering playbook to the public. They released 12 courses that were internal-only until this week. This covers LLMs, Robotics, and MCP, which is the exact tech stack behind Llama, Mistral, and every major open model. This level of training won't stay free forever. Here's what you need to grab right now 👇

🚨 BREAKING: Someone just built a tool that generates and visualizes complex 3d particle systems just by typing a prompt. You tell it what you want, it builds the physics, and you export the react or three.js code instantly. 100% Free.

This is insane 😳 Most people are just using AI tools Very few actually understand how they work So I collected Stanford’s complete LLM curriculum and turned it into a step-by-step learning path Worth over $500 Giving it away free for the first 4,500 people Transformers → Training → Alignment → Agents → Evaluation Study this once and you’ll stop guessing with prompts and start thinking like a real AI engineer How to get it: Follow must (so i can dm you) Rt and comment 'LLM'

The best AI courses that are FREE to learn in 2026: 1. Anthropic: anthropic.skilljar.com 2. Google: grow.google/ai 3. Meta: ai.meta.com/resources 4. NVIDIA: developer.nvidia.com/trainin… (GOATed) 5. Microsoft: learn.microsoft.com/training 6. OpenAI: academy.openai.com 7. IBM: skillsbuild.org 8. AWS: skillbuilder.aws 9. DeepLearningAI: deeplearning.ai 10. Hugging Face: huggingface.co/learn 11. FastAI: course.fast.ai 12. Kaggle Learn: kaggle.com/learn 13. Stanford AI: cs231n.stanford.edu 14. MIT OpenCourseWare: ocw.mit.edu 15. Full Stack Deep Learning: fullstackdeeplearning.com 16. DeepMind Resources: deepmind.com/learning-resour… 17. OpenAI Cookbook: github.com/openai/openai-coo… 18. Papers With Code: paperswithcode.com 19. AssemblyAI Blog: assemblyai.com/blog 20. Pinecone Learn: learn.pinecone.io Never pay for AI courses. The best ones from the industry LEADERS are already completely free.

A reporter spent two years digging into OpenAI and came back with the one conclusion Silicon Valley would rather bury. Everyone who helped build the place next to Sam Altman eventually walked away with the same aftertaste: used. 300 interviews. 90 people from inside OpenAI. Same shape to every story. Back in 2015, Altman needed Elon Musk in the room to make OpenAI real. Musk was fixated on AI as an extinction-level risk. So Altman published a post framing AI as the greatest threat to humanity. Funny thing: right before that, his go-to nightmare was engineered pandemics - not AI. His public philosophy snapped into perfect alignment with Musk’s, almost overnight. Money arrived. Musk co-founded. Then Altman found a way to edge him out. Dario Amodei left and built Anthropic. Ilya Sutskever pushed to remove Altman said he shouldn’t be the one anywhere near the AGI “button.” Mira Murati left and launched Thinking Machines Lab. There isn’t another tech giant where the entire founding bench exits and spins up rival shops. Not Google. Not Apple. Not Meta. No one. In Congress: AGI is the miracle that ends cancer and poverty. In Redmond: AGI is a $100B machine. For the public: AGI is the smartest assistant you’ll ever have. Three stories, one product. Whoever he’s facing gets the version that unlocks a yes. The world’s biggest AI company wasn’t assembled by breakthroughs alone. It was assembled by one person’s talent for telling every audience exactly what they were hoping to hear. And the unsettling part is: it worked.

Instead of watching netflix lock in and master AI automation in 1 hour! Build workflows, connect tools, and level up your productivity with n8n no code needed.

The guy who shipped 3 AI agents at Google I/O 2025 just open-sourced his 424-page design playbook. Production-ready code for 21 patterns across the entire stack Free via Google Drive

Big news for developers! Grok Code Fast 1 is now available in Visual Studio. This advanced AI model brings smarter, faster coding assistance right into your favorite IDEs via GitHub Copilot Chat. Available in public preview for Copilot Pro, Pro , Business, and Enterprise plans, Grok Code Fast 1 supports agent, ask, and edit modes, making coding more intuitive and efficient. 👉 Admins: Enable the Grok Code Fast 1 policy in Copilot settings to unlock access for your team. 🔗 Read the full changelog to learn more and get started: msft.it/6016sIhco #AIcoding #GitHubCopilot

1. Data Scientist toolbox : Give Away Alert!! 1. Artificial Intelligence 2. Machine Learning 3. Cloud Computing 4. Ethical Hacking 5. Data Analytics 6. AWS Certified 7. Data Science 8. BIG DATA 9. Python 10 MBA For 24 Hours only! To get it: 1. Like, Retweet and Follow 2. Reply "Send"

The job of a startup is to find undiscovered talent and distill it into a product.

10 Data Analytics projects for job interview success in: 1. Microsoft Excel. 2. Power BI. 3. Tableau. 4. SQL. 5. Python. 6. R. Dataset and source code provided 👇:

10 GitHub repos to sleep with as an ai engineer covering ML systems, Agents, RAG, MLOps: 1. Machine Learning for Beginners by Microsoft → Start here if you’re brand new to ML. Covers basic ML concepts in Jupyter notebooks beginner-friendly and visual. 🔗 lnkd.in/gGithBVP 2. Learn PyTorch for Deep Learning → A great repo to learn PyTorch - could be a bit outdated but the concepts still applies. 🔗 lnkd.in/d4ptSuUY 3. Hands-on Large Language Models → This repo supports the Hands-On LLM book. Learn everything from basic language models to finetuning with real notebooks. 🔗 lnkd.in/gpvPemeG 4. AI Agents for Beginners → A fantastic beginner-friendly course to get started with AI agents. Free 11-lesson hands-on curriculum - no fluff, just code. 🔗 lnkd.in/gVm5gmv7 5. Prompt Engineering Guide → One-stop-shop for prompt engineering. Guides, papers, lectures, and tons of curated examples. 🔗 lnkd.in/gDt3Sknr 6. LLM Course → Hands-on course covering the entire LLM lifecycle — design to deployment. Includes roadmaps Colab notebooks. 🔗 lnkd.in/gUPJmWNM 7. GenAI Agents → Great tutorials code for building agent-based LLM systems. Covers everything from simple tool-using agents to advanced workflows. 🔗 lnkd.in/gaiZgzpA 8. RAG Techniques → One of the most comprehensive and dynamic collections of Retrieval-Augmented Generation (RAG) tutorials available 🔗 lnkd.in/dcGtjFgY 9. Made With ML → Covers full ML product lifecycle: from design to CI/CD and monitoring. If you’re serious about building production-grade ML systems, this is gold. 🔗 lnkd.in/gn2RhT_m 10. Designing Machine Learning Systems → Summaries code diagrams from the popular O’Reilly book. A must-read if you want to architect real-world ML pipelines. 🔗 lnkd.in/g26KNXfb Credit to @shirin_kjam for the list 🤘🏻