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Checklist Applied Machine Learning (at FF MUNI)

Before the course starts

  • propagation via community channels
    • discord FI
    • facebook "Study Group FI MUNI"
    • facebook "Filozofická fakulta MU Brno"
    • facebook "PLIŇáci"
  • propagation via official channels
    • Red Hat channels
    • facebook "FI MUNI" (?difficult but if we can do it once, it will be repeatable?)
  • send email to previous students
    • invite them come to guest lectures
    • ask them to spread info about course and emphase to tell the true (so newcomers are not suprised)
    • mention what will be different/better (so they know that their feedback have value)

After the course starts

  • ask datacamp for free access for students (usually it take less than week)

Before each session

  • take a look at datacamp deadlines (so we can ask students who are late)
  • watch materials again (so we are on the same boat as students)
  • (optional) prepare activity to ensure that they have read/watch materials

After each session

  • enter activity points (AP) to information system
    • 1 AP per activity, add the name of the activity to notes
  • (new) list of all activities "somewhere" and current maximum reachable AP (in 2022, it was not clear how far are students from the maximum)
  • enter datacamp assignement
  • send e-mail
    • send it one day later (so students have time to recover a bit before new tasks)
    • summary from last live session (describe activities ?and their reasoning?)
    • describe datacamp tasks with deadline (+2 weeks are default)
    • describe materials that should student read/watch
    • mention project milestone deadlines
    • give info about guest in advance (2 week & 1 week before)

After the oral exam

  • ask student for feedback
    • improvements
    • what was the worst/most boring/... activity
    • what she/he likes the most
    • is there something that was missing