Build a Local LLM App in Python with Just 2 Lines of Code
Ready to become a certified Certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdbdaL Learn more about Large Language Models (LLMs) here → https://ibm.biz/Bdbda9 Two lines of code is all it takes to program a large language model locally! 🤯 Distinguished Engineer Chris Hay demonstrates how to run LLMs on your machine using Python and async programming. Learn tips for efficient setup, multi-turn conversations, and persona customization. 🚀 AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdbdaC #llm #python #aidevelopment

▶︎
Using Large Language Models | Build Your Own LLM Workshop #1

▶︎
RAG vs Agentic AI: How LLMs Connect Data for Smarter AI

▶︎
Python Full Course for Beginners

▶︎
Building Decision Agents with LLMs & Machine Learning Models

▶︎
RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models

▶︎
Don't learn AI Agents without Learning these Fundamentals

▶︎
The Ultimate Guide to Local AI and AI Agents (The Future is Here)

▶︎
Transformers, the tech behind LLMs | Deep Learning Chapter 5

▶︎
The Ultimate MCP Crash Course - Build From Scratch

▶︎
MCP vs API: Why traditional APIs are failing AI agents

▶︎
A2A Protocol (Agent2Agent) Explained: How AI Agents Collaborate

▶︎
How AI agents & Claude skills work (Clearly Explained)

▶︎
Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker

▶︎
Orchestrating Complex AI Workflows with AI Agents & LLMs

▶︎
LLM Course – Build a Semantic Book Recommender (Python, OpenAI, LangChain, Gradio)

▶︎
What AI Agent Skills Are and How They Work

▶︎
He Risked Everything To Warn You: No One Is Ready For What's Coming, And The AI Companies Know It!

▶︎
Only Video That Will Make You BETTER at MATH - 100%

▶︎
How to Build a Production-Ready RAG AI Agent in Python (Step-by-Step)

▶︎
