Learn AI with KodeKloud - AI Agents for Beginners – Part 1 (Free Labs)

🧪Hands-On Labs for Free: https://kode.wiki/4sp4FMT 🤖 AI Agents for Beginners - Part 1 (First Half Free on YouTube!) | KodeKloud Want to build AI agents but don't know where to start? This is the first half of KodeKloud's complete AI Agents for Beginners course available FREE right here on YouTube. The full course (Part 2) is coming soon exclusively on KodeKloud.com! No fluff. No jargon walls. Just clear, hands-on learning from scratch starting with how ChatGPT actually works, all the way to building tool-calling agents in Python. ───────────────────────────────────────── 📌 WHAT YOU'LL LEARN IN THIS VIDEO ───────────────────────────────────────── ✅ What ChatGPT is and how GPT (Generative Pre-Trained Transformer) works ✅ How Large Language Models (LLMs) learn from billions of text examples ✅ Tokens & Tokenization - the currency of every LLM interaction ✅ Temperature & Sampling - controlling randomness and creativity in AI outputs ✅ Context Windows - the LLM's working memory and its hard limits ✅ Prompting Techniques - zero-shot, few-shot, chain-of-thought, and role-based prompting ✅ Your first LLM API call in Python (just 7 lines of code!) ✅ AI Workflows vs. AI Agents ✅ When to use workflows vs. agents in production system 🧪 FREE HANDS-ON LABS INCLUDED - https://kode.wiki/4sp4FMT Practice building agents in a real sandbox environment with no credit card, no surprise charges. API keys, cloud environments, and everything you need are already set up. 🚧 FULL COURSE NOW LIVE ON KODEKLOUD The complete AI Agents For Beginners: OpenClaw Case Study course is now available! Dive into agent implementation, multi-agent systems, memory & reasoning strategies, and the 🦀OpenClaw open-source agent case study — all in one place. 👉 Start the Full Course: https://kode.wiki/4c3ozpO ⏱️ TIMESTAMPS 00:00 – Introduction & Course Overview 02:41 – What is ChatGPT? (GPT Explained) 08:30 – How Large Language Models (LLMs) Work 14:30 – Tokens & Tokenization 20:17 – Temperature & Sampling 22:53 – Context Windows 27:52 – Prompting Techniques 35:09 – Your First LLM Call 38:35 – Lab 1: Your first API call in Python 41:47 – When to use an LLM 45:00 – Roles and Messages 47:57 – Section 2: Architecture 48:51 – What are Tools? 51:34 – Tool Integration 52:54 – Lab 2: Build a Tool-Calling Application 54:59 – AI Workflows 57:34 – Workflows vs. Agents (The Key Difference) 1:00:58 – When to Use Workflows vs. Agents 1:00:58 – Conclusion #AIAgents #buildaiagents #LLMTutorial #AIForBeginners #ChatGPT #PromptEngineering #LargeLanguageModels #GenerativeAI #PythonAI #KodeKloud #ToolCalling #AIWorkflows #ContextWindow #Tokenization #MachineLearning #AIEngineering #MultiAgentSystems #DeepLearning #AIArchitecture #GPT #AIForDevelopers #FreeAICourse #BuildAIAgents