Learn the basics of Python in a simple, practical way designed for people who want to build AI applications. This course helps you understand core Python concepts step by step, so you can confidently move toward working with data, automation, and AI tools.

Most agents fail not because the model is weak, but because nothing controls what they're allowed to do. See how NeMo Guardrails sets the boundaries: filtering unsafe or off-topic queries, managing user intent to keep the bot on-task, and applying output controls so responses stay on-policy. Hand-drawn diagrams break it down step by step. Part 1 of 3 · Secure AI Agents — Foundations. Full eval, memory & agent build covered live in the AI Accelerator Bootcamp.

Learn why public LLM rankings are not enough for real-world AI applications. This beginner-friendly video explains how to evaluate AI models using your own company data, with a simple introduction to key metrics like faithfulness, relevance, retrieval, and correctness. Perfect for anyone building RAG systems, AI applications, or production LLM workflows and wants to make better model decisions based on real performance, not generic benchmarks.

Follow structured, practical learning journeys designed to help you build the right skills in the right order. Explore Data and AI foundations, prompt and context engineering, AI application development, agentic systems, career pathways, projects, and leadership. Each path combines curated lessons, practical resources, exercises, and real-world guidance to help you progress from learning AI concepts to applying them confidently.

Access recordings from our practical AI, data science, GenAI, agentic AI, career, and application-building workshops. Each recording includes real-world concepts, demonstrations, tools, frameworks, and implementation guidance to help you learn at your own pace and apply the knowledge to practical projects.