Workplan and Coaching
You’ll start working on your project – an end-to-end, fully automated research workflow – in the first course week. The activities below help you to structure your project. Stick to the plan to ensure you can finish the project in time.
Planning
| Week | Project Stage | Working on | Deliverable/Feedback on |
|---|---|---|---|
| 1 | No team work yet | Explore whom you would like to collaborate with (team formation). | |
| 2 | Data Exploration | Pick data set and come up with suitable research question, start exploring data using RMarkdown. | Register teams on Canvas & Coaching #1 - Grading details → 1.1 (Research Motivation) and 2.1 (Data Exploration) |
| 3 | GitHub | Set up repository on GitHub using the course-dprep organization, initialize
GitHub Issues and Project Board (columns “backlog”, and the current sprint’s “to do’s”, “in progress”, and “done”), commit initial readme.md with research question and initialize directories, continue exploring and auditing data, and committing files throughout using the command line/terminal | Coaching #2 - Grading details → 1.2 (Repository Structure), 1.3 (Way of working using GitHub) |
| 4 | Data preparation | Preparing your dataset for analysis. | Coaching #3 - Grading details → 2.2 (Data Preparation), 1.3 (Way of working using GitHub) |
| 5 | Automation | Start automating your pipeline and refine source code. | Coaching #4 - Grading details → 3.1 and 3.2 (Source code quality and degree of automation) |
| 6 | Analysis and Deployment | Refine source code and analysis | Coaching #5/6 - Grading details → 2.3 (Analysis and deployment) |
| 7 | Wrap-up | Conduct final housekeeping checks | Optional feedback meetings |