Counts as:

Normally Offered:

Each Fall

Campus/Online:

On-campus only

Requisites:

ECE 30010, ECE 56500

Requisites by Topic:

A broad and strong foundation in undergraduate computer systems, computer architecture, and machine learning courses, and good programming skills.

Catalog Description:

The objective of this new course is to facilitate research at the intersection of Cloud Computing and Machine Learning (ML). Today, ML is fueling pivotal applications spanning from face recognition to autonomous vehicles. While ML is powerful, deploying ML models in real-world scenarios while achieving optimal performance presents numerous challenges. Recent advancements in software and hardware platforms have made rapid progress in ML algorithms. This course will explore the latest developments in cloud computing systems, considering the emerging new ML algorithms, and applications that are driven by them. We will also examine the application of ML techniques for optimizing various aspects of cloud computing systems. The course will cover essential background on ML and cloud computing systems, and we will engage in the discussion of papers from recent conferences that focus on (a) leveraging ML for diverse optimizations across the systems stack, and (b) building systems to facilitate the deployment of emerging ML models in real-world settings.

Lecture Outline:

Assessment Method:

Projects, presentations (3/2024)