Agentic Application Delopment leveraging LLMs and RAG and Open-Source Frameworks

Agentic AI is one of the hottest topics in the IT industry and beyond. It represents a significant evolution in AI, enabling systems to operate with a high degree of autonomy by reasoning, planning, using tools, executing tasks, and adapting to changing conditions with minimal human intervention. This course provides participants with practical, hands-on experience in designing and developing Agentic AI solutions. They will build multi-agent systems, agentic RAG applications, and custom AI tools while working with popular frameworks such as CrewAI, LangGraph, AutoGen, and PydanticAI. Through real-world projects, participants learn how to turn Agentic AI concepts into practical solutions with tangible business value. The learning path provides a structured progression from fundamental agent concepts to advanced agentic architectures. Participants learn how agents can collaborate, reason, make decisions, use external tools, interact with knowledge sources, and execute complex, multi-step workflows. Each project builds on previously acquired knowledge while introducing new frameworks, techniques, and architectural patterns. The course is particularly valuable for professionals who want to develop AI applications capable of complex decision-making, multi-step problem solving, autonomous task execution, and dynamic adaptation to changing circumstances. By the end of the course, participants will have both a solid conceptual understanding of Agentic AI and practical experience building agentic applications with modern frameworks.