STAT 3250

This is a new course that the Statistics Department offered this semester. I think they are offering this course since Python is language that is easy to learn and has useful statistical libraries that might help you in the real world. There were many bumps since it was the first semester Holt was teaching this new course, such as extensions and general expectations. I wish he can make the course better by making the homework questions much more clearer or by giving out the answers(output) first so that we know what we should expect in our coding, just like how it is done in CS 1110. I don't know when this will be offered again, but if you want to learn coding in Python and do statistical analysis, this class is for you.

If you have experience with Python from CS 1110, it is pretty simple for the first month or so. You will be better prepared than anyone else in the class. Taking CS 1110 before taking this class helped me immensely. I recommend taking CS 1110 first. After the first month, the class picks up the pace. You learn how to use statistical libraries such as Numpy, Pandas, DataFrames, and etc. You use these libraries to clean data, analyze data, and perform calculations by writing out code in Python. The last two months are quite challenging since you have to deal with massive data sets and the questions that Holt makes up is sometimes unclear. He is open ended in how you interpret the questions as the semester moves on, but as I said, it would be better if he made the questions more concise and clearer.

Overall, it is very similar to a CS course--homework is all coding and the exam is reading code and writing code. Pretty good class and you learn a lot but there are some homework that is insane and take a lot of time. Be ready to stare at the computer for hours which composes of looking at the given data sets, try different things by writing small bits of code and testing it.

Two midterm exams. The best way to prepare for exams are to look at his sample questions that are released before the exam. The exam is very similar to the sample questions. Make sure you know how to do all the sample questions, then you will at least get a B. There is a final group project. It really comes down how well your group is determined but I honestly am not a fan of group projects for some reason since I like to be in control of all the code and analysis. It's a personal thing, but I hope he gets rid of the final project with a final exam or move it to an earlier date where you don't have to be obsessed and stressed with the project and other final exams.

Overall, its not a bad course. I learned a lot. I had experience with Python in CS 1110 and did well in CS 1110, so it was easier to pick up the material and coding part. I may be a bit biased since I loved Python as my first programming language, but I loved learning how to use statistical libraries in Python by applying loops, conditionals that I learned in CS 1110 for doing statistical analysis. If you do not like coding, you might figure out that you should drop the course early on. It is very easy for the first month, but if you are struggling I recommend dropping it since you should be aware that the homework is not that simple as was in the first month since it involves a lot of effort and time to look at data sets and perform calculations by writing code.

This class is definitely easy for someone who has experience with coding in any language, but might be tricky for someone with no programming background at all. The homework can be difficult some times but it is graded very leniently. I wish Professor Holt would make lecture some how required to attend since he is super nice and knowledgeable. Overall, not hard to get an A, and you will learn quite a bit about coding and statistics.

This is a very heavily coding based class, so if you have any background in coding, it definitely makes it easier to learn and pick up things, but Holt does assume that some students are learning Python for the first time. This course focused more on data cleaning/manipulation so that it was be easier to use rather than statistical analyses. There was classwork due every week and homework every two weeks. Classwork was generally straightforward to the python examples he showed in class, and homeworks sometimes were more difficult, but graded pretty loosely.
Two midterm exams and one final group project. Exams were straightforward and similar to the practice exam that was posted on collab. The group project was the only groupwork during the semester and was the 'final'.

This course is one of the best I've taken at UVA in terms of real-world applicability. Python is a super easy language to learn (coming from a guy with no coding experience before this class) and Professor Holt is a diamond in the rough in the Statistics Department. Course is 12 assignments, no exams and no final. You can work with others on the assignments but it is best to try to do the assignments on your own before getting help from others. It's basically like solving a puzzle, which I really enjoyed, and nothing is overly complex. One assignment towards the end of the course will be very tough, so be ready for that. Overall though, I decided to take this class on a whim and it ended up being my favorite class of the semester. Your grade will be exactly what you put into the course, but expect to work a fair amount to get that A. DON'T USE FOR LOOPS UNLESS HE SAYS YOU CAN USE FOR LOOPS. After like assignment 4 or 5, he bans for loops unless in very specific circumstances. Don't try to argue with him if you use one and he docks points. Get used to not using for loops, groupby and masking are honestly easier and faster. This is usually an issue with people who don't go to lecture, so go to lecture. Also, Professor Holt has people turn in assignments on Wednesdays in class. A significant number of people every week would come into the class halfway through Professor Holt's lecture, walk to the front of the class to turn in the assignment, then straight-up leave the class immediately. Not only is this fundamentally rude, it got on Professor Holt's (everyone else's) nerves. So, do yourself a favor and wait until the end of the class to turn it in if you absolutely need to turn in the assignment late for some reason. He's super chill about it and won't mark you off points. In fact, he'll respect you more.

I highly recommend this class to anyone who is interested. The class starts with basic coding know how and progresses into various data manipulation "puzzle" type assignments that pretty much boil down to manipulating data frames. The typical knock on a class like this is that everything could be learned via online tutorials and one would be better off taking a more rigorous class, but I still think that it is worth taking. The assignments are very well crafted and I now would feel very comfortable tackling a multitude data manipulation oriented problems.

To E-school kids: This is an introductory coding class that requires no prior experience. If you are taking this just to learn some Pandas/get an easy A then please don't complain about how easy the class is. No one cares.

Great class, teaches you a lot about how to use python for data manipulation. The other comments here which are longer are accurate if you read those. If you are worried about it overlapping with intro CS it doesn't, the content differs and you will continue to learn new things. You learn new functions, new libraries (Pandas, Numpy, and Plotly) and also get experience coding using a different wrapper i.e. Spyder

I highly recommend this class. It is an extremely interesting class if you are at all interested in statistics/computer science/data science and is extremely applicable in the real world. The course involves just 12 homework assignments, each of which covers slightly different topics (pandas, bumpy, statistics concepts, some data visualization). The homework start off easy but get pretty long and more difficult at the end (though never too bad). If you work with other students and go to the TA office hours, it is not hard to do well in this class. Finally, I will say this class was one of the most rewarding classes I have taken at UVA.

Professor Holt is the nicest man you will ever meet in your life. The class however is kind of wonky. Spring 2019 he made the class 12 assignments and 3 exams which progressively got harder. At the beginning of the semester he said no loops, but then on the last exam and assignments all the questions required loops. However i don't think the class was that hard. Its a hard A but easy A-. you need a 95 to get an A. Overall good class and would recommend.

Professors Holt is great and I couldn't recommend this class more! For the Spring of 2019 he changed the course from the old 15 assignment format so that the grading consisted of 9 assignments and 3 exams. The first exam was an in class open internet, open notes exam that wasn't too challenging but the time constraint certainly made it difficult to complete the entire exam. Holt moved away from this format for the next two exams making them essentially the same as the homework assignments just longer and slightly more challenging. Another great thing about this course is attendance is far from necessary. Holt posts all his notes online and if you have taken a previous coding course (CS1100 perhaps) you will certainly not need to go to class everyday as we don't learn anything that challenging. All in all, I can't recommend this course enough I learned a lot and for any aspiring data analyst the applications of python that this class teaches are very useful.

Best class I have taken at UVA. It is so useful and Holt is the man! Can't recommend enough!