Reviews

One of the best courses I've ever taken, in any subject, at any school. Learned a ton about performance considerations in parallel computation and had to actually solve serious problems in the projects. The workload is intense. I spent 25-30 hours every single week for the entire semester on this course. However, every project is a seriously interesting implementation problem and taught me a lot. The lectures are excellent, and the TA and professor were very active on Piazza answering questions and resolving issues. Some of the project instructions were a bit rough/vague, but the high level of engagement from the TA and professor more than made up for that. No exams, just projects.

Pros: 1. Good soft intro to using R for data wrangling, viz, and a little regression modeling and PCA 2. Lectures are interesting 3. Content is well organized and easy to follow 4. TAs, Dr. Wilke and fellow students are all highly engaged Cons: 1. Only uses R, ggplot. A survey of other viz tools might be a good use of a class week. 2. Did not cover dashboarding best practices. Detailed Review: I enjoyed this class and found it immediately helpful in my job. Sometimes in industry you cannot pick the tools you use for viz, so a short survey of tools one may encounter might have been useful (i.e. Tableau, Looker, Plotly, Matplotlib, PowerBI, etc.). The course is also focused mainly on individual plots, which fits well to viz for research and analysis. There is little covering dashboarding practices.

Pros: 1. The instructor, Claus Wilke, is an expert in data visualization and his lectures are concise and engaging. 2. The class is very well organized and the grading criteria is explained clearly. 3. The course covers a lot of useful material while still having a manageable workload. Cons: None This is one of the easier classes in the program but it is also one of the most informative and polished classes as well. The professor is truly an expert in data visualization and it was a pleasure learning from his wealth of experience. His lectures are very engaging as he has excellent communication skills and a good sense of humor. The R programming language is used heavily throughout the class but the emphasis is on how to use the ggplot package. All of the R knowledge you need to be successful in the course is provided in the lectures. The professor is the author of the free, web-based textbook used in the course but because the lectures were of such high quality, I never needed to consult the textbook and rarely needed to consult outside references such as Stack Overflow. All of the lecture slides are available to view on the course website and the code used to generate the slides (R Markdown) is also provided in a GitHub repository. All of the homework assignments and projects are peer-graded but I had no issues with the grading. The grading criteria is explained clearly and is somewhat lenient so you should have no problem getting an A in the class if you follow the instructions. If you need help, you can post your question on Piazza and the TAs or the instructor will respond quickly. I was impressed by how active Professor Wilke was on Piazza. Overall, this is a great class. I learned a lot and the workload was very manageable. To provide context for my review, I received an A in the class.

Pros: 1. Great class. You will learn a lot and get exposure to a ton of languages. 2. No test or quizzes just a couple of projects. 3. Lectures are clear and the projects are fun. Cons: 1. You need to spend a lot of time on the projects. They can easily take 20-40 hours. Overall: A great course

Pros: 1. Your programming skills will absolutely improve. 2. You'll never again be tempted to debug via print statements. 3. You'll have a solid grasp of fundamental data structures coming out of the course. Cons: 1. --- 2. --- 3. --- Detailed Review: I really liked this course, even though I've scarcely ever worked harder to pull off a "B" than I did here. Professor Lin is great. The lectures are great, the quizzes are fiendishly difficult, but fair, and the projects are challenging, relevant, and geared at turning you into a better programmer than you were coming into the course. For me, at least, this goal was more than achieved. I know the course can be really challenging, especially in the second half. But fear not - there's a generous curve, and everyone who really puts in the effort in the end does well. Lin is a great professor and a really decent guy...just work hard and you'll learn a lot in the course and (with the curve) come out with a passing grade.

Pros: 1. Extremely good video lectures 2. Theory heavy, but the theory is the baseline for almost all advanced computation 3. Still has applied programming Cons: 1. Front-loaded difficulty curve makes it difficult to pair up with another course at the start 2. It is still Matlab (which we get a university license for, but still... index starts at 1) 3. Honestly, not many cons, and only the first one is meaningful Detailed Review: This course has the best lectures of any of the courses I've taken so far. The professors cadence and environment just worked for me. Maybe I'm old-school like that. Also, if you are uncertain if you are ready, the undergrad prep is available for free online

Excellent class. All of the course materials can be found here: http://www.philkr.net/dl_class/material

Detailed Review: Pros: 1. High quality lectures, clear example code 2. TA's really responsive on Ed 3. Homework fairly easy, exams are essentially take home Cons: 1. Lighter on theory 2. 3. Detailed Review: Overall, this was a really well-delivered class. Prof. Parast's lectures are well-paced and clear, with accompanying lecture notes and thoroughly documented R code. She gives a good overview of biostatistical concepts, though she occasionally hints at their applications in other disciplines, like economics. Not a con, per se, but compared to other classes in this program, it's lighter on the theory. She doesn't always elaborate on the inner workings of some of the more complex R functions and packages, though she does an excellent job of describing their applications. The TA's were really helpful on Ed, especially the lead TA who provided detailed answers, often with links and citations, to every question, including the more involved ones. The 6 homework assignments were mostly simple (i.e. 15 questions of basic definitions, calculations, and R programming), and the lowest grade gets dropped. I thought the midterm and cumulative final were considerably more difficult. Many of the questions either required additional steps and calculations compared to the homework or weren't covered in the homework at all, but I thought they were overall fair. There's a 48-hour window to complete both exams, and they don't have to be finished in one sitting. Overall, the workload was fairly manageable, at the lighter end for this program, but I still felt like I learned a considerable amount.

Pros: 1. Covers a lot of topics and concepts 2. TA office hours almost every day and varying times from 1000 CST to 2000 CST 3. Solid community and support from peers Cons: 1. It honestly required pre-requisite background knowledge, but can be overcome if you do not have it (it just costs time) 2. Guidance for exams was a shot-gun blast. It changed day-to-day on Piazza. 3. I'm not a fan of swapping out instructors halfway through. It makes it feel like 2 semesters smashed into one. Detailed Review: For context, I have a non-CS/non-Math undergrad. If I'm lucky I'll end up with a B- because it has been drinking from a fire-hose trying to catch up on probability and statistics, calculus, and linear algebra (in that order). The first half of the course was painful because I could not follow along with any of the mathematical concepts, but I was able to obtain a conceptual understanding that saved me in the mid-term. I probably spend at least 20 hours/week during the first half of the course. Prepping for the midterm I probably spend 50-60 hours/week. In the second half, the course was immensely easier. I probably spent an honest 10 hours/week or less. In the first half, I was busy digesting tons of background mathematical knowledge that was required so the second half made a bit more sense. The homework was rough. I attended almost every TA session during the first half of the course. In the second half, I attend a TA session maybe 1-3 times per week and was able to complete all the assignments. Again, I do not have the background to do the mathematical proofs and that was where I really struggled. Some of the programming assignments were difficult for me to pick-up, but ultimately fairly trivial. The support of the class is what really made me enjoy it. Having Slack and Discord to talk and discuss the topics helped a ton. We had a study group that really made a difference and started building a little community. I did not do well with solely Piazza because I felt like I could not intelligently convey what I was struggling with through written language. I was stuck in a "You don't know what you don't know" type of loop. Thankfully, discussing the topics with peers really helped a ton. The Piazza was definitely there if you needed it thought. The textbook was only used for the first half. The second half had a draft textbook for free. I used both books extensively along with numerous other resources like 3blue1brown and StatQuest.

This class was awesome. It's one of the best taught classes in the program. I loved the enthusiasm put by the teachers and the content is of great quality. I found this course not too easy but it was probably due to my background and my college experiences. I surely learnt a lot about proof by induction! If you put the effort needed is probably easy peasy.