ECE 657A DKMA

Data and Knowledge Modelling and Analysis - Mark Crowley - University of Waterloo

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.

news

Mar 28, 2022 March 28 Announcements -- Updates on Asg3, Midterm Grades, Remaining Classes, Final Exam
Mar 3, 2022 March 3 Announcements -- Updates on Asg2, Lecture Links
Feb 21, 2022 Feb 21 Announcements -- Updates on Asg1 Evaluation, Asg2 release, Midterm
Feb 7, 2022 Feb 7 Announcements -- Updates on Asg1 Evaluation, Asg2 release, in-person classes, midterm
Jan 26, 2022 In-Person Classes -- Information about in-person classes beginning on Feb 7, in-person midterm

selected publications

The primary resources that could be useful are listed here, but there is no required texbook for the course. For a (nearly) complete list of the reference used in slides throughout the course see the Course Zotero Reference Group page.