Key Features of the Project:

Students choose and propose topics

• You may work by yourself in a team of one
• But working in small groups of two, three, four, five, ... is encouraged and preferred
• There is no perfect group size but three or four worked well for many teams
• We allow single-person teams but recommend teams of three or four

Everything on GitHub

• You should also use git (via your project's GitHub repository) for your intermediate steps
• i.e. do not just upload finished work but all steps

Submissions must 'run;

• Your end result is code that must do something sensible with data
• Possible tasks for data are gathering, cleaning, aggregating, modeling, estimating, visualizing, summarizing ... and any combination thereof

Write-up in Markdown

• Which should rendered nicely at GitHub, inclusion of figures or charts for visualisation is encouraged
• You can choose html or pdf as the final format (note that pdf requires latex at your end)
• No powerpoint, no keynote

Final Deliverables

• The actual project plan and idea manifested in actual code
• The actual project description in a write-up in markdown, i.e. a short paper
• The actual project presentation recorded via Zoom or alike (more details forthcoming)

May contain multiple course components:

• Pick from shell, sql, markdown, R, ...
• But your work should focus and center around R and different R packages
• "anything that runs on 'morrow', our RStudio Server", goes
• Please avoid technologies we cannot deploy there
• i.e. GPU-heavy deep learners may be out; cpu-based ones may work if installable
• so in a nutshell if you can install it from CRAN and deploy it on RStudio, you can use it