The field of Artificial Intelligence intersects many areas of knowledge which engineers can utilize for building robust, dynamic systems in a world filled with large amounts of data yet also containing uncertainty and hidden information. In this course we focus from the ground up on the concepts and skills needed to build systems that can reason, learn and make decisions using probabilistic reasoning. This begins with reviewing concepts from Bayesian probability and learning how to perform probabilistic inference efficiently with MCMC and variational methods. We will discuss the classic...
Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.
This is an entry-level course on computer programming for engineering students. Its central aim is to equip students with foundational knowledge on how to instruct a computer to carry out various functional operations. Through a combination of lectures, hands-on exercises, and programming mini-projects, students will actively learn:
how a computer works in terms of executing functional tasks and parsing operational instructions
how instructions can be written in a language that is comprehensible by a computer.
Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.
This course provides an introduction to the analysis and design of algorithms. Algorithms are at the very foundations of computing. It is important to understand how to design them, and analyse them for correctness and efficiency. It is also very important to able to recognize whether a given problem is intractable so you don’t naively seek efficient solutions where none may exist. This course will introduce you to a broad set of different types of computational problems and the most well known algorithms for solving them. Along the way we will learn how to prove the correctness of...
This course provides an introduction to the analysis and design of algorithms. Algorithms are at the very foundations of computing. It is important to understand how to design them, and analyse them for correctness and efficiency. It is also very important to able to recognize whether a given problem is intractable so you don’t naively seek efficient solutions where none may exist. This course will introduce you to a broad set of different types of computational problems and the most well known algorithms for solving them. Along the way we will learn how to prove the correctness of...
