Engineers encounter data in many of their tasks, whether the sources of this data may be from 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 from it and to know how to act on it. In this course you will learn the fundamental tools for assessing, preparing and analyzing data. You will learn to design a data and analysis pipeline to move from raw data to task solution. You will learn to implement a variety of analytical and machine learning algorithms to including supervised, unsupervised and other learning approaches. Students will gain practical experience with coding and analysis through assignments. Research students will have opportunity to connect course material to their research as a project instead of some of the assignments.
|Nov 15, 2021||
Course Welcome -- Initial information about the course, Lecture 1 and a student survey to fill in.