Optimize Agentic AI: Algorithms for Peak Performance is an intermediate course for AI practitioners and engineers aiming to build fast, scalable, and responsive agentic systems. In the real world, an AI agent's intelligence is useless if it is too slow. This course equips learners with the tools to diagnose and solve these critical performance bottlenecks.

You will learn to master essential algorithm optimization techniques, moving beyond slow, brute-force methods. Through hands-on labs, you will replace baseline planners with sophisticated informed search algorithms such as beam search and quantitatively measure the dramatic improvements in planning time. You will also learn to analyze the computational complexity of multi-tool reasoning pipelines using Big-O notation, using profilers to pinpoint the exact functions and data structures that create system slowdowns. By the end of the course, you will not only be able to implement critical optimizations—such as using an index to reduce complexity from O(n²) to O(log n)—but also to write a professional technical proposal to justify your engineering decisions.