Explore how systolic arrays accelerate AI workloads, enabling efficient parallel processing for neural networks and modern AI hardware.

Learn how neural networks work, from perceptrons to deep learning, and why multiply-accumulate operations drive modern AI computing.

Introduction to artificial intelligence, tracing its history, core principles, and how neural networks enable computers to learn and make decisions.

Course module exploring AI hardware acceleration and ASIC design techniques for machine learning applications.

Introduction to neural networks and how machine learning models process data using layered computational structures.

Learn how logistic regression models classify data and support machine learning applications in engineering and analytics.

Introduction to linear regression and how statistical models predict relationships between variables in engineering data.

Overview of artificial intelligence concepts and how AI workloads drive new semiconductor hardware architectures.

Learn how high electron mobility transistors (HEMTs) enable high-speed, high-frequency performance in modern semiconductor and microelectronics systems.