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Syllabus: Programming Practices for Research Students

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All materials are licensed under a Creative Commons CC-BY-SA license. The license allows you to copy, remix and redistribute any of our publicly available materials, under the condition that you attribute the work (details in the license) and do not make profits from it. More information is available here

Suggested Citation

The suggested citation for the course materials is:

Lachlan Deer and Julian Langer, 2021, Syllabus for Programming Practices for Research in Economics, University of Zurich

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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syllabus's Issues

2019 Course Material - sketch

Here's a sketch of what we (@bergmul and @lachlandeer ) talked about on Skype.

Let's iterate here as needed. I've put @bergmul 's name on material I assume he can teach, feel free to change it based on your comfort level.

Monday Tuesday Wednesday Thursday Friday
Week 1
Morning Terminal Version Control Version Control Basic Python Python: Numpy
@bergmul @bergmul @bergmul @lachlandeer @lachlandeer
Afternoon Terminal Version Control Basic Python Basic Python Python: Pandas
@bergmul @lachlandeer @lachlandeer @lachlandeer @lachlandeer
Week 2
Morning Python: SciPy Python: Metrics Advanced Python Python Project R: Basics
@lachlandeer @lachlandeer @lachlandeer @lachlandeer @bergmul
Afternoon Python: Plotting Python: Webscraping Python Project R: Basics R: Data Analy.
@lachlandeer @lachlandeer @lachlandeer @bergmul @bergmul
Week 3
Morning R: Plotting R: Econometrics R Project Build Tools Build Tools
@bergmul @lachlandeer @bergmul @bergmul @lachlandeer
Afternoon R: Econometrics Advanced R R Project Build Tools Build Tools
@lachlandeer @bergmul @bergmul @bergmul @lachlandeer

Some thoughts my me:

  • Could we move git later (post python?) get's everyone coding early then they might see the need for version control as we develop some stuff, then we introduce it
  • what for the third person to do?
    • Could they lead the project sessions in R, Python and Snakemake? If we essentially sketch it up they can steer it? Or we can make them figure out a good exercise (passing it my us of course ... )
    • Would give them exposure to all of the tools to help them take a bigger lead in following years

Let me know what you think!

L

update motivation

check over motivation part of syllabus to make sure the narrative is still in line with both:

  1. how we fell about the state of the world
  2. what we think this course is doing

foundations/advanced vs full course split

We are potentially facing two sets of students (from UZH)

  • those that took JL and I's 'foundation course' in 2019
  • first years that didnt do the above

Question is how we want to set up syllabus etc to deal with this and make it clear which parts of the course are relevant to each set of people.

Two immediate thoughts emerge

  1. bold face (or similar) the material that is similar so that those who did the foundations stuff don't need to attend
  2. separate syllabi for each group
    • there's a stack of overlap if we go this way which is frustrating

@lachlandeer prefers route 1.

archive 2017 edition

similar to #5 , we need to archive the 2017 edition in a branch + release

the most recent commit 948f816 is the 2017 edition update

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