• Pandas and Data Analysis
• Data Visualization

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

• 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, organise it on the spreadsheet
• Teachers support students to conduct projects
• Set of questions

• 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

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

• 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.

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.

• Lecture Material
• Project Instruction

• Lecture Material
• Exercise

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

• Lecture Material
• Project Instruction

• Lecture Material
• Project Instruction

• Lecture Material
• Project Instruction

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.

• Lecture Slides
• Lecture Material
• Project Instruction

• Lecture Material
• Project Instruction: Rentals
• Project Instruction: Checkars

• Lecture Material
• Project Instruction: Rentals
• Project Instruction: Checkars

• Lecture Material
• Project Instruction
• Project: csv file
• Project: scraped cleaned.pkl

• Project Instruction
• Project: Readme
• Project: SO Survey 2020
• Project: Survey Results csv