Building GenAI Applications with Llama 4

Generative AI is evolving rapidly, and open-weights models are at the forefront of this revolution. This course provides a clear, text-based guide to building powerful applications using the advanced capabilities of Llama 4. You will explore how to work with extended context windows and process multimodal inputs to build intelligent, responsive systems. By reading through this comprehensive guide, you will transition from understanding core AI concepts to implementing robust application architectures. You will learn how to structure prompts for complex reasoning, handle diverse data formats, and optimize model performance for real-world scenarios. What you'll learn: - Understand the foundational architecture and capabilities of Llama 4 open models - Implement multimodal processing to handle both text and visual inputs effectively - Manage long-context windows for deep document analysis and multi-turn conversations - Configure API integrations and utilize developer tools for seamless deployment - Apply prompt engineering techniques to maximize reasoning and output quality - Design retrieval-augmented generation patterns to ground your applications in custom data We begin with essential terminology and the fundamentals of open-weights models before guiding you step-by-step through application design, API configuration, and advanced integration patterns. This structured approach ensures you build a solid theoretical foundation before exploring practical implementation details. This course is designed for software developers, product builders, and technology enthusiasts who want to learn how to build with modern open AI models. No prior experience with generative AI development is required, though a basic understanding of programming concepts will help you get the most out of the technical examples. Start reading today to master the next generation of open-weights AI development.