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Data Analytics coure in ReDI School NRW

What you learn

  • Pandas and Data Analysis
  • Data Visualization

Learning process

  • Lecture -> Project -> Review
  • Each lesson takes place with one presenting teacher and one support teacher

How do we conduct projects?

  • Students work either with the Google's Colab or the JuperLab
  • One project per week (we have 9 modules for 24 lessons)
  • 3-4 students per group
  • Teachers support students to conduct projects
  • Set of questions

Peer review

Why reviewing?

  • We at the ReDI School students learn together and thrive together
  • Peer review is about giving feedback
  • Peer review is about understanding your peers’ code

How to review

Keep in mind:

  • Be positive: We are here to learn and to thrive together
  • Peer review has take place while group members are present
  • Give constructive feedback

Check if your team is ready for review

  • Go into the breakout room of the team
  • Team shares their screen and explains code and conclusions
  • Fill out the review section
  • Give them feedback on their code and conclusions.

Curriculum outline

1. Kick-off

For projects:

  1. Copy your Colab/JupiterLab link and paste it into the spreadsheet for your team
  2. Mark it as ready for review once you are done with it
  3. Correct the Colab/JupiterLab of the team you have to correct once they are done.

2. Statistics

3. Pandas

3-1. Intro to Pandas

In this session, we will work on filtering datasets and grouping according to variables to get aggregated data.

3-2. Pandas Transformation

4. Data Structures

Visualization

5. Intro to Analytical Thinking and Plots

We will show you a few libraries to visualize data and, in the meantime, we will start introducing you to the art of data analytics.

6. EDA

7. Storytelling and dashboards

8. Cleaning Data / Handling missing data

9. EDA & Analytical Thinking

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