REPL VS papers-I-read

Yes you can as long as there are no progression blockers. Check the GitHub https://github.com/world-class/REPL

An example: “REPL” is a learning hub made by students at the University of London’s computer science program (Goldsmith) REPL

BSc CS is also a very promising degree, except that I find UoL BSc to be on the weaker side with Calculus and Linear Algebra being absent, so are operating systems and computer architecture classes. They also equate some IBM data science courses on Coursera to 2 of their 3rd year classes. You can check out their CS curriculum on GitHub https://github.com/world-class/REPL/tree/master/modules. It is also taught by Goldsmiths University, a creative arts university.

As already mentioned, the exams are currently held online, however they are planning to start the in-exam-center exams from next semester. Normally you can have maximum of 4 modules per semester, so that makes it maximum 4 in-person exams per semester. Take in account that not all modules require exams and some of them are project based. More info about which modules require exam and other useful info about the course can be found here https://world-class.github.io/REPL/ 😉

You can find the syllabus for both subjects here Discrete Math and Computational Math. In general, I would strongly recommend using our REPL, which contains a lot of info about modules and also notes from student which are very useful :)

Looks like you miss a lot of things but you're enrolled, don't worry though, but I do suggest you take time to read through the FAQ in the REPL as much as possible. Pretty much everything you need to know (more than you asked) is there.

Also, for more details about this degree, you could go to : https://world-class.github.io/REPL/ This is a student run website which has a lot of info about the degree.

Suggest you go read this, as its an answered question - https://world-class.github.io/REPL/

Take a look at the REPL. https://github.com/world-class/REPL/tree/master/modules/level-4/

It is simply impossible to keep track of all publications. The Reddit branches listed above will help to isolate the most important texts (since the author became the head of the AI ​​department at Tesla, the site began to break more often, but it’s still the best tool). There is also such a list of articles with comments and recordings of webinars from the YouTube channel Kaggle with parsing of scientific articles related to data science algorithms.