Here are most of the courses I have attended along with a few words and possibly with notes, assignments, and/or exams attached – I do not account for any errors or quality however, as some might have been done last minute:)

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Attended in 2021, TA’ed in 2022. The introductory programming class at DIKU is mainly in F#, but as of 2022 it also includes a bit of python to wrap up with. Jon Sporring (main lecturer) has created his own book/notes for the course. An easy course for those who have programmed before, but will be difficult for those who have never. Everyone passes this class if you put in the time/effort! No grade, just passed/not passed.

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Covers basic math to be used in many other courses to come. Grading is done by considering some assignments and two small tests. Typically the test questions are similar to other years, so it is possible to just grind the old tests. There exist good notes that have been sent from older to younger students, ask your tutor/TA for it.

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Covers basic macro-/micro economics. A bit weird class, and assignments are very difficult, as many are confused about what is going on. Usually, the assignments remind a lot of the previous year’s assignments. Class is just passed/not passed based on the assignments.

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Covers basic statistics and probability subjects. First in a series of 3 course that covers econometrics, which are super interesting but also tough courses. Many people fail this course (30-50%), but there are also many exams to read up on from the economics course. The course contains some assignments that must be done to take the exam. The exam was 4 hours in hand with only notes

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Attended in 2022, TA’ed in 2023. Taught in English, since the lecturer is from Sweden. A course with many different topics from discrete math, proof methods, algorithms, complexity analysis, and formula languages. It can be overwhelming to begin with, but a really fun and interesting course that formalizes computer science. Many of the concepts will be used in later courses. The course contains some assignments that must to completed to take the exam. The exam is also handwritten with only notes. The course will change to “introduktion til diskret matematik” from 2024.

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A fun and very good class. Good lectures and a lot of good old video recordings of lectures. The assignments are not particularly difficult but can be very time-consuming and include coding in Python (or F# if you really like that?). Assignments are graded and taken into account in the final grade, as well as two smaller tests in hand with only notes.

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First “real” economics course, and finally makes some of the concepts make sense. Did not contain assignments, but I believe it does now. The course makes use of basic python for the coding in jupyter notebook. The exam was a 96-hour take-home exam and graded.

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Includes many different topics, and is in general quite a good course. Lectures can be a bit boring, but there are many really good old lecture recordings (as well as random YouTube videos on the topics). Many of the topics will also be used in later courses. The exam is oral without preparation, with about 8-10 min to present and then 5 min of questions. There were 8 topics, and all were given 2-3 weeks before the exam. Probably the most time-consuming exam I’ve prepared for, as you had to be extremely prepared to cover all topic material in only 8 min. There are also assignments, but the coding part did not count for anything, which I found a bit strange.

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Introduces econometrics using basic methods such as OLS and uses stata (they did talk about changing to Python). Quite a good course, but it gets quite difficult fast. It is really good to maintain intuition throughout the course, as that helps a lot with understanding the results of a regression. Definitely, one of the most useful courses if you want to pursue economics (and to be ready for econometrics B). The exam was an intense 12-hour group take-home exam.

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Introduces the basic sollow model, and basically just builds on that. A bit confusing to begin with, but many of the derivations are basically the same with just 1 or 2 more symbols. The math was really easy on the exam and way easier than the older exams we used to prepare. The exam was 4 hours written in hand only with notes.

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The courses mainly focus on “doing things fast” using knowledge about memory, parallel programming, caching, etc. I thought it was a really fun course, but requires a lot of time to do the assignments 100%. The course uses C as the main programming language (which can be a bit annoying at times), but also a bit of Python for the server part. The exam is a long 5 days take-home exam, but can be done quickly of you really work hard.

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Did not follow the course lectures, as I was TA’ing for DMFS. I did watch some old recordings, which were okay. Quite a good course, but also quite demanding to prepare for, as there are many topics and algorithms. There are required assignments, but they used the same each year, we decided not to prioritize them, but I think they still provided good intuition about important concepts. The exam was 4 hours in hand with only notes. Consisted of some multiple-choice questions, and then a written part (some proofs and such).

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The last course of econometrics on the bachelor – and probably the most difficult one so far. The course covers a lot of different methods and topics. It is all very interesting, but it can be tough to fully understand everything. The exam was however much more manageable, so don’t get too discouraged. The course uses Python and has good lectures (though the pace is quick). I regret not having used the open offices that Jesper had, as it could have cleared up a lot of questions easily. The exam is a 48-hour group take-home exam and was much different than the assignments made. The grading is a bit different in this course, as 50% of it is the exam given 48 hours to complete, and the other 50% is a randomly chosen old assignment that you get to resubmit (so do have both assignments ready to submit).

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The course covers relations calculus (RC), relations algebra (RA), and finally PostgreSQL (as well as other minor topics). To get good at this course, basically just write as many queries as possible in RC, RA, and SQL as that is 90% of the exam. The course has 2 assignments and a large project (the project sadly does not count for anything though). The exam is 4 hours in hand with only notes.

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The course is mainly game theory and is probably the best course we’ve had so far. The lecturer Anders is fantastic and covers the material in a logical and yet intuitive way. As preparation for each lecture, Anders uploads a couple of different videos to watch, which are highly recommended to watch! The exam is a 48-hour take-home exam, and does require a lot of work.

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The course is mostly about philosophical questions, ethics, and other more abstract subjects. The exam was divided into a one-hour 20-question multiple choice exam and a 10 min video you had 24 hours to submit.

The course introduces a lot of different macroeconomic theories, such as AS/AD curves, and relations between monetary policies, inflation rates, interest rates, etc. The course covers a lot of material, and imo does become a bit boring. Exam was a take home 48 hour exam.

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Written together with Thomas and with Bertel Schjerning as supervisor. Our thesis uses the Berry-Levinsohn-Pakes (BLP) estimation framework by implementing random coefficient logit demand models with IV regression to correct endogeneity, combined with a Bertrand-Nash oligopoly model on the supply side, to estimate demand, marginal costs, markups, and counterfactual merger and breakup scenarios in the U.S. automobile market

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First machine learning course on UCPH. Teaches a lot of general ML techniques, and introduces learning theory and generalization bounds. The course has weekly assignments, thus quite a high workload. The exam is a 1-week take-home exam.

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The notorious first mandatory course in the CS master’s. The course introduces a lot of advanced techniques, and everything is programmed in Haskell. The course has weekly assignments, thus also quite a big workload (increases throughout the course). The course is not a difficult as in other years, as most people pass now. I spent some time before getting familiar with functional programming, which I do recommend doing. They do post a lot of good tips on GitHub. The exam is a 1-week take-home exam.

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The course introduces a lot of different deep learning methods and techniques, and is quite hands-on with weekly assignments, which count for your grade, as it is a continuous assessment course. Medium workload, but not too bad. Quite a beneficial course, which I did enjoy.

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Second mandatory course in the CS master’s. Introduces many different advanced topics such as computational complexity (P/NP), randomized/approximation algorithms, linear programming, and others. Quite many and advanced things, which do not all relate to each other, thus quite a big curriculum. The exam is a open book 4 hour exam, and was honestly quite difficult.

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