Turn your ideas into visuals by mastering the art of text-to-image generation. This workshop introduces participants to state-of-the-art diffusion models and shows how to build powerful image-generation pipelines using the Diffusers library. From simple text prompts to advanced techniques like ControlNet and LoRA adapters, you’ll learn how to guide AI in creating expressive, high-quality images for artistic and practical applications.

Learn how to move beyond chatbots and build AI agents that can reason, take actions, and connect to real-world data and tools. In this hands-on workshop, you’ll explore the ReAct paradigm (reasoning + action), understand the new Model Context Protocol (MCP) standard, and implement a simple end-to-end AI agent using Gemini CLI and open-source technologies.

Ship custom ML and generative models without wrestling with DevOps. In this hands-on workshop, you’ll use Modal — a serverless compute platform for AI and data workloads — to define infrastructure in Python, run on-demand CPU/GPU hardware, and scale from one request to hundreds of workers in seconds. You’ll learn Modal’s core concepts, compare CPU vs. GPU execution, explore parallelism patterns, and deploy a production-style Stable Diffusion inference pipeline.

Go beyond traditional scraping techniques and learn how to build next-generation web scrapers powered by large language models. Combine the precision of established tools with the flexibility of AI to extract data, interpret content, and automate complex web interactions.