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Learn to build LLM-based agents using DSPy through a comprehensive hands-on approach that covers everything from basic prompt programming to advanced agentic systems. Master the fundamentals of DSPy with 8 practical examples that demonstrate effective prompt programming techniques. Develop expertise in context engineering, progressing from basic concepts to professional-level implementation through fully hands-on exercises. Discover how to create Retrieval Augmented Generation (RAG) pipelines that deliver reliable results in real-world applications. Build your own long-term agentic memory system for LLMs using Mem0, implementing the complete solution from scratch within the DSPy framework. Gain practical experience in generative and agentic AI development through step-by-step guidance that transforms theoretical knowledge into working applications.
