Timeplan

This page contains a schedule of the teaching sessions. Most of the teaching will take place August 01-12, 2022, with additional supervision on August 16. Each day will generally contain one-two teaching sessions. Most sessions will follow the daily schedule below:

  • Morning session (9-12):
    • 9-10 Live lecture,
    • 10-12 Notebook with integrated lecturing videos on technical aspects of the session + exercises
  • Lunch break (12-13):
  • Afternoon session (13-16):
    • 13-14 Live lecture,
    • 14-16 Notebook with integrated lecturing videos on technical aspects of the session + exercises
  • Office hour, optional: 16-17 (booking system through Google Sheets, see link in the schedule below)

The complete schedule of sessions is listed below with title, lecturer and links to material. Unless otherwise specified, the teaching will use the hours specified above. See practical information for where lectures and exercise classes take place.

Date Time Title Teachers Material
——- Preparation ——-
Jun 27 Assignment 0 posted nb
Jul 28 12:00 Assignment 0 hand-in abs
——— Week 1 ———
Aug 01 9-11 1a. Course welcome + intro to git and markdown ABN/TGC/HFB pdf
11-12 1b. Meet group TAs/TGC/HFB
13-16 2. Data Structuring 1 TGC & TAs le , nb , nb_sol
Aug 02 9-12 3. Data Structuring 2 TGC & TAs le , nb, nb_sol
13-16 4. Plotting TGC & TAs le , nb, nb_sol
16-17 Office Hour TGC gs
23:59 Assignment 1 posted – nb
Aug 03 9-12 5. Strings, Queries and APIs TGC & TAs le , nb , nb_sol
13-16 6. Scraping 1 HFB & TAs le, nb , nb_sol
Aug 04 9-12 7. Scraping 2 HFB & TAs le, nb , nb_sol
13:59 Fill in supervision sheet – pdf, gs
14-16 TA help + supervision * TAs pdf, gs
Aug 05 9-11 9. Data Ethics ABN pdf
14-16 TA help + supervision * TAs gs
Aug 05 23:59 Assignment 1 hand-in - abs
Aug 08 9-12 8. Scraping 3 HFB & TAs le, nb, nb_sol
13-16 Exam talk + TA help + Supervision HFB & TAs le, gs
16-17 Office Hour HFB gs
Aug 09 9-12 10. ML Introduction TGC & TAs le, nb, nb_sol
13-16 11. Regression and Regularization TGC & TAs le, nb , nb_sol
23:59 Assignment 2 posted – nb
Aug 10 9-12 12. Model Selection and Cross-validation TGC & TAs le, nb , nb_sol
12-13 Office Hour TGC gs
13-16 13. Performance Metrics, Non-linear ML, and Perspectives TGC & TAs le
Aug 11 9-12 14. Text as Data HFB & TAs le, nb , nb_sol
12-13 Office Hour HFB gs
14-16 TA help * TAs All previous material
Aug 12 9-12 Exam talk + TA help + Supervision TGC & TAs nb
14-16 TA help + supervision * TAs gs
23:59 Assignment 2 hand-in abs
——— Week 3 ———
Aug 15 10-12 Supervision 3 * TAs gs
Aug 15 20:00 Exam project description due pdf, abs
Aug 23 10:00 Hand-in Exam on Digital Exam

* : optional participation

Main lecturers

Teaching assistants (TAs)

  • Jonas Skjold Raaschou-Pedersen (JSRP)
  • Mischa Püschl Bennedsen (MPB)
  • Magnus Lindgaard Nielsen (MLN)
  • Lasse Ramovic Laustrup (LRL)

Download material using Github Desktop

  • Download Github Desktop and make a Github account.

  • Open Github Desktop and go to File -> Open Repository

  • Go to the URL-tab and choose the course Github page (isdsucph/isds2022), and where you want to save it on your own computer.

  • Now you can access the files on you own computer.

  • If there have been updates to the ISDS-repository on GitHub, you can update it (known as pull, sync or fetch) in GitHub Desktop by choosing ISDS as your Current repository and press Fetch origin.

  • NB! When you make changes to your Notebooks, make a copy of the file, with a now name. Else you risk overwriting your changes, the next time you update the repository.

Legend

  • {le, nb, sol}: Respectively refer to lecture slides, exercises / assignment and solution to exercises in Jupyter Notebook format
  • pdf: Slides in PDF format or just PDF file
  • gs: Google Sheets link
  • abs: Link to Absalon