Teaching Approach#

This course was designed from the ground up as an online course, with optional in-person labs. The initial impetus for this was the COVID-19 pandemic, and associated lockdown. The need for the course was evident prior to the pandemic, but the need for online courses to fulfil a laboratory component in our curriculum proved to be the tipping point for me to start actually creating the course. A course in data science naturally lends itself to online teaching, because all of the tools rely on equipment that students almost universally already have at home: a computer. Recognizing that not everyone has a particularly powerful computer, however, this class will rely on cloud computing resources — so the particular specifications of your computer shouldn’t matter much, as long as you have decent internet access.

As you saw in the course learning objectives, this course aims to provide you with training not only in working with data, but in working on projects in a team-based virtual/remote working environment. Already, this form of working was common for people in tech-related fields, and many software and tech companies support remote working by their employees. We can only expect this to be more common in the post-pandemic world, so this course will provide you with practical experience and skills for the future of work.

Since this is the first online course I have ever designed or taught, I have engaged in extensive research on best practices for online teaching. It turns out, many of these are really best practices in teaching, period. The online environment has forced instructional designers to address issues such as students participating asynchronously (rather than all showing up for class at a designated time), distractions, short attention spans, and even the nature of how students’ work is assessed. Embracing these best practices creates a very different course than you have likely encountered before — and hopefully one that is more engaging and enjoyable in the process!


This course is also taught from a fundamental premise that might be different than you have experienced before. I assume that you are taking this course because you genuinely want to meet the stated learning objectives of the course. That is to say, you are not taking this course just because you need a credit towards your degree, or because you think it will improve your GPA. Moreover, one of the learning objectives of this course is that by the end, you will be able to demonstrate a professional work ethic. Although this is a university course, it is framed to emulate a professional work environment. This means that you are expected to take responsibility for your own learning and performance, and also to support the learning and performance of your peers.

You should not view the members of the teaching team (instructor, TA) as opponents, but as guides and consultants. Although ultimately we will assign each of you a grade, our primary role is to support your learning, and help you achieve your best possible performance. At the same time, you should not expect that the teaching team will give you everything you need to succeed — a key part of taking responsibility for your own learning and performance is that you actively engage in finding the information you need, and teaching yourself how to do things, often through trial and error. The teaching team is not here to give you all the answers; rather, we are here to provide you with the skills to learn and find the answers you need. This may involve finding documentation, tutorials, and examples on the web, talking with your peers, or asking specific questions of the teaching team — questions that demonstrate that you’ve already tried to solve the problem yourself, and have identified the thing that you’re stuck on. This is to say, you should not view the course instructor as a “sage on the stage” (especially since there is no stage), but rather as your “guide on the side”.