Preparation

ImportantMaterials

See Nextcloud (lecture_x)

Tasks

• Include “must-learn” markers: <!-- _class: must_learn -->
• Consistently include “vocabulary” sections at the end (like in regression 1)
• Create first-slide background illustrations for all sessions (consistent design) - see https://github.com/fs-ise/analytics-and-big-data/pull/2
• Align learning objectives in individual sessions with the overall overview
• Link checker and spellchecker set up (slides / notes / exercises)
• Consistency of terminology across sessions
• We may prepare the handout generated based on all slides.
• Syllabus updated
• License, code of conduct, contributing, …
• Test exercise sheets: GitHub JupyterLab with pre-installation of pandas etc. and PDF generation
• Update requirements (exam):
  • show and read code for the analysis
  • include code reading and interpretation, maybe even pseudo code writing in the exam (and exercises)
  • surveys during the lecture: vote for “additional exercise/more difficult exercise”