Optimize and Benchmark AI Algorithms for Speed

In this course, you’ll learn how to analyze and benchmark AI-related algorithms so your systems run efficiently at scale. You’ll use computational complexity and data-structure behavior to predict performance as workloads grow, then validate those predictions with small prototype implementations. You’ll learn how to design fair benchmarks, interpret results using metrics like latency, throughput, memory, and scaling curves, and make defensible decisions when trade-offs are unavoidable. By the end, you’ll be able to identify bottlenecks, communicate performance findings clearly, and choose the best-performing approach for real-world AI workloads using reproducible measurement.