Agentic AI Coding

🤖 85 Useful AI TOOLS... ➡️ Share

🔗 Most ML roadmaps

If you’re tired of bloated diagrams and endless theory, this one’s for you.

This is the 10-step roadmap I wish someone gave me earlier focused on real-world impact, not just flashy model builds. Swipe through to see: ✅ The core skills you actually need ✅ What separates you from junior talent ✅ What most self-taught engineers skip Whether you’re transitioning from data analyst, coming from software dev, or just trying to stop tutorial-hopping...

🔅 AI Engineering in 76 Minutes (Complete Course/Speedrun!)

All images are from the book AI Engineering unless otherwise credited.

⏰ Timestamps 00:00 What is AI Engineering? 01:49 Understanding Foundation Models 08:40 Evaluating AI Models 14:50 Model Selection 23:15 Prompt Engineering 30:20 RAG and Context Construction 36:56 Agents and Memory Systems 43:02 Finetuning 52:40 Dataset Engineering 59:45 Inference Optimization 01:09:01 Architecture and User Feedback

🔗 How to use Machine Learning to predict fraud

🔗 AI Agents ✅ An AI agent roadmap outlines the steps and skills needed to develop and deploy autonomous AI systems. ✅ This includes foundational skills in programming, AI/ML concepts, and data handling, progressing to more advanced topics like NLP, LLMs, and agentic frameworks. ✅ The roadmap also emphasizes practical experience through projects, community engagement, and potentially, internships or open-source contributions.

📚 AI Engineering: Building Applications with Foundation Models 1st Original Price: 57$

AI is getting out of hand 😂 Baby Joe and Baby Theo Von

🔗 Life-cycle of Machine Learning Model

ChatGPT users send 2.5 billion prompts a day https://news.nzokolab.com/chatgpt-users-send-2-5-billion-prompts-a-day-2409.html