Teaching / Programming for ERIM PhD students (2013)
This is the course page for Programming (ERIM), academic year 2013-14, block 2.
Lecture slides in pdf:
- #1 / 2013-10-15
- #2 / 2013-10-22
- #3 / 2013-10-29
- #4 / 2013-11-07
- #6 / 2013-11-19
- #7 / 2013-11-26
- #8 / 2013-12-03
- #9 / 2013-12-10
- #10 / Open parallel computing lecture
Exercises will be posted here and in blackboard. The answers _must_ be submitted via blackboard. When submitting your answer, include all the source files in a zip, and upload that through blackboard's exercise completion functionality. Note that the solution you submit must consist solely of the source files that are executable independently.
I recommend getting used to the command prompt of your chosen language as it includes functionalities commonly available in text-based user environments (for example, browsing command history with up- and down arrows). Note that you can use the command prompt also for showing function documentation with command help (e.g. 'help fprintf' in Matlab, '? print' in R), and for finding function names with lookfor (e.g. 'lookfor print' in Matlab, '?? print' in R).
Exercises in pdf:
- #1: deadline 2013-10-27 23:59 CET
- #2: deadline 2013-11-03 23:59 CET
- #3: deadline 2013-11-13 23:59 CET
- #4: deadline 2013-11-25 23:59 CET
- #5: deadline 2013-12-02 23:59 CET
- #6: deadline 2013-12-09 23:59 CET
- #7: deadline 2013-12-16 23:59 CET
There are 8 exercises (one / week during weeks 2-9). Each awards 12.5% of the final grade. The exercises are graded according to the following scheme:
- Up to 10% from completing the exercise succesfully. Code that does not run awards _always_ 0% from the whole exercise - do not submit crap. If you manage to complete only part of the exercise, submit it and state clearly in comments which part you did and which not
- 2.5% for code clarity (functions, indenting, comments, variable names)
Data files used in the exercises:
Additional learning material:
- Introduction to Programming with R for all you useRs.
- LN-TT-22012-3, the lecture notes from the Programming for Econometricians course.
- Internet is full of tutorials to programming in all possible languages. For example, see Wikiversity.
- Fun (at least IMHO) mathematical programming assignments can be found in the Project Euler. These are good learning material also for others than the pre-master students.
- The official Matlab learning resources page has a lot of (Matlab) learning material available.