Week 0 — Pre-Class Welcome
Week 0 — Pre-Class Welcome#
Hello, and welcome to CS 533! This page isn’t really a course week — it’s a quick orientation so you can know what to expect in our class, and things to do if you want to start preparing ahead.
This week has 0h8m of video and 0 words of assigned readings.
Welcome to class!
This is a flipped classroom course. Online videos — like the one you just watched — along with various readings are the primary content delivery mechanism. We’ll use our course time for engaging with and practicing the material together.
There are several reasons for this design. First, it uses our time together in the virtual or physical classroom for things that can only, or at least optimally, be done in a synchronous environment; pushing the lectures out to video makes more time for collaborative practice and engagement. Second, having the content online will make it easier to review the material for assignments and exams, and to catch up if you miss time due to illness or other concerns.
On Thursday of each week, there will be an in-class quiz over the lectures and readings. Some weeks, it may be over a portion of the material; in such cases, I will clearly mark the cutpoint for the quiz.
Syllabus and Schedule#
Two key documents for the semester:
You will need to plan your time in order to succeed in this class.
There are 7 real assignments (A1–7), each intended to take approximately 8–10 hours over 2 weeks. They may take you more or less time, depending on how quickly the material and requirements click for you. Assignments will come at a steady pace, though — there is no big end-of-term project.
Each week has approximately 75–90 minutes of video content, plus readings. To help you plan, I provide the length of each video and most of the readings (reading lengths denoted in words).
You may need to spend some additional time studying and practicing material, although our in-class time will hopefully help with a lot of that.
Study and practice are necessary to be a competent data scientist. There are no shortcuts to expertise. My goal with this class is to give you a solid, well-practiced foundation for the core technologies and techniques you will need in the rest of your data science education and work.
If you want to get started early, some things you can do:
The course web site is pre-populated with the content from last year so you can look ahead for what to expect; this year will be quite similar, but I am also making some revisions. Each page has an alert banner that I will remove once I have reviewed and revised that page for this year.
I welcome your feedback throughout the course on what’s working for you and things that might need adjustment. Please send me a message on Piazza or e-mail me.