Optimization Across Classical, AI & Quantum Computing

Optimization is at the heart of many of today's most complex challenges, from logistics and materials discovery to artificial intelligence and scientific research. This course explores how classical computing, artificial intelligence, quantum computing, and hybrid approaches can be used to address optimization problems across a range of real-world applications. Through foundational instruction, expert perspectives, technical demonstrations, applied examples, and knowledge checks, you will examine how optimization problems are formulated, compare the strengths and limitations of different computational approaches, and explore emerging quantum and AI-based methods. The course also examines the software, hardware, and high-performance computing infrastructure that supports modern quantum workflows. By the end of the course, you will be able to evaluate different approaches to optimization, identify when emerging technologies may offer value, and apply a consistent framework for examining new computational methods and claims.