An overview of the courses in this minor. Time flows from top to bottom: periods 1, 2, and 3.
The course links for this year are as follows. Please register on time for each course separately in SIS. Also, please register to the coordinator for the minor as a whole here!
- Scientific programming (6 EC; Python). This will be taught in period 1 under a different name, the course code for this is still being created. The tentative name of the course will be “Python for Data Processing” according to my last information. If (and only if) you are already proficient in basic programming in Python (think: functions, lists, dictionaries) then you may also take a different programming course, either more advanced or for different programming languages. Other useful languages used in computational science include Mathematica, Matlab, or C/C++ (for high-performance).
- A math course which fulfills one or more of your math deficiencies: probability theory (P), calculus (C), and linear algebra (L). P is most important, closely followed by C, and then L at modest distance. Possibilities include the courses listed below. The coordinators of the courses (period 1 only) listed below have given their approval for accepting Minor CLS students. Important: please first enter/edit your math elective choice in the following Doodle to ensure the below-mentioned maximum numbers per course:
Enter your math elective choice on “https://doodle.com/poll/ dh8z7pmzitypew4c” (note the space inserted in this link to prevent scraping and spamming). Please obey any capacity constraints mentioned below. Register through SIS only after filling in this Doodle. When you change your choice for the elective then please update your entry in this Doodle accordingly. Please enter your full name in this Doodle. Only the Minor coordinator can see your name. We need to send these names to the course coordinators so that they can anticipate the extra influx. Unfortunately this is the state of the art of the administrative system.
- Mathematics 1: Calculus. Important: this course only accepts 5 students from the Minor CLS. Use the above-mentioned Doodle to find out if you are among the first 5 for this course, and register your choice there. If not then please select another course. The deadline for registering for this course using the Doodle is June 1! Wiskunde B background or equivalent is required!
- Calculus 1 (VU) (taught by Swarttouw). This course is hosted at the VU, and permission is granted by the course coordinator to allow 5 students from this minor;
- Any other math course which has at least one of P, C, and L as its focal points;
- Note that there are many options for suitable math courses, but most of them are not strictly in period 1. There are courses placed in other periods or spread over multiple periods. If you plan to take the minor in a single year then this will be difficult, but if you have more time then you may consider finding a suitable course in a different period. (We did not ‘pre-book’ any seats in such courses so please contact the course coordinator on your own to check if it is alright with him/her.)
- Also, some are not 6 EC. For instance, you could take Wiskunde voor chemici 3 in period 1 but it is 3 EC so you would have to find another 3 EC course. Across all periods the choices are legion, but restricted to period 1 an example would be Wiskunde 1A. (Neither of these courses have been asked a priori to admit minor students, please directly contact the relevant coordinators yourself to ask permission. It often depends on the background of the student.)
- You may also propose your own interdisciplinary elective in case you already have a solid basis of probabilities, calculus, and linear algebra: always contact the coordinator in that case and propose one or two course titles. Think for instance of (introductory) computer science subjects such as computer systems or algorithms & complexity, to give non-informatics students more insight into the more technical side of computational science.
- If you are still missing one of P, C, L but you would still like to take (or are forced to take) a different interdisciplinary course, then please have a look at the online resources down below to remedy your math skills on your own. This is not a formal requirement built into the minor, but highly recommended for you to get the most out of the minor.
- Turning Points in the Natural Sciences is for instance a good interdisciplinary choice regardless of your background.
- Modelling and Simulation.
- Scientific Data Analysis.
- Project Computational Science.
Further pointers for registration:
- For registering for Basisprogramma PML: Basisvaardigheden Wiskunde, Statistiek & Programmeren (I guess now: Basic Skills in Mathematics, Statistics & Programming ) you apparently need to fill in this form and turn it in to the listed address. Also you may want to contact the study advisor of the program to make sure that you are eligible.
If you are for whatever reason unable to adequately cover one of the math domains (P, C, L) in period 1 then please have a look at some corresponding online courses or instruction videos to at least get the basics before you begin the courses in period 2. This is not a formal requirement built into the minor program, nevertheless it is highly recommended to brush up on one or more of your math skills in order for you to get the most out of the minor.
Short instruction videos are for example:
- Khan Academy on probability theory.
- 3Blue1Brown videos on calculus.
- 3Blue1Brown videos on linear algebra.
Or better yet, online courses (or equivalent):
- Calculus (differentiating, integrating), something like https://www.coursera.org/learn/calculus1 or even Ordinary Differential Equations basics, such as https://www.coursera.org/learn/ordinary-differential-equations
- Python programming experience, e.g. Datacamp or a Python programming course on Coursera.
- Linear algebra introduction, maybe something like https://www.coursera.org/learn/linear-algebra-machine-learning which also uses some Python
- Probability theory (‘kansrekening’) introduction, maybe something like https://www.coursera.org/learn/probability-intro (but programs in R, not Python) or https://www.coursera.org/learn/introductiontoprobability