Agentic AI Crash Course (github.com)

A new crash course on agentic AI aims to enlighten practitioners on the distinctions between generative and agentic AI, highlighting their core capabilities and applications in real-world scenarios. This course covers essential topics such as workflow agents, semi-autonomous systems, and decision frameworks, along with model integration strategies like Retrieval-Augmented Generation (RAG) and performance optimization techniques. Participants will also explore advanced reasoning capabilities, multi-agent architectures, and case studies representing successful enterprise implementations, which inform the design and evaluation of agentic AI applications. The significance of this course lies in its focus on enabling enterprises to harness the full potential of agentic AI, promoting the development of applications that go beyond traditional software design. By addressing emerging technologies, industry roadmaps, and practical case studies, the course equips AI professionals with the knowledge necessary to create scalable, efficient systems that integrate seamlessly into existing infrastructures. With the growing demand for sophisticated AI solutions in the enterprise sector, this crash course represents a vital opportunity for practitioners to stay ahead in this rapidly evolving landscape.