Overview Learn about the fundamentals of Artificial Intelligence in this introductory graduate-level course. It provides a survey of various topics in the field along with in-depth discussion of foundational concepts such as classical search, probability, machine learning, logic and planning. Syllabus
Overview This course is designed to teach you about managing application containers, using Kubernetes. We’ve built this course in partnership with experts such as Kelsey Hightower and Carter Morgan from Google and Netflix’s former Cloud Architect, Adrian Cockcroft (current Technology Fellow at Battery Ventures), who provide critical learning throughout the course. Mastering highly resilient and …
Overview Learn foundational machine learning skills in the Intro to Machine Learning Nanodegree program and learn how to apply these skills to a variety of tasks. In the Machine Learning Engineer Nanodegree program, learn how to create a machine learning product and deploy machine learning models to a production environment, such as a web application.In …
Overview The goal of this course is to give you solid foundations for developing, analyzing, and implementing parallel and locality-efficient algorithms. This course focuses on theoretical underpinnings. To give a practical feeling for how algorithms map to and behave on real systems, we will supplement algorithmic theory with hands-on exercises on modern HPC systems, such …
Overview The course covers the basics of Memory Systems, File Systems, Multithreaded Programming, and Networking. Together these form a strong foundation from which the student can understand cutting edge research in the areas of Virtualization, Distributed Systems, and Internet-scale services in the GT Advanced Operating Systems sequence. Syllabus
Overview This is a graduate-level course in the design and analysis of algorithms. We study techniques for the design of algorithms (such as dynamic programming) and algorithms for fundamental problems (such as fast Fourier transform or FFT). In addition, we study computational intractability, specifically, the theory of NP-completeness. The main topics covered in the course …
Overview In this program, you’ll work with the Bitcoin and Ethereum protocols, build projects for real-world application, and gain the essential skills for a career in this dynamic space. Syllabus
Overview Ever played the Kevin Bacon game? This class will show you how it works by giving you an introduction to the design and analysis of algorithms, enabling you to discover how individuals are connected. Syllabus
Overview Cyber-physical systems, such as automobiles, cars, and medical devices, comprise both a physical part and a software part, whereby the physical part of the system sends information about itself to the software part, and the software sends information, usually in the form of commands, to the physical part. Physical systems have “a life of …
Overview In this class you will learn how to debug programs systematically, how to automate the debugging process and build several automated debugging tools in Python. Syllabus
