Code overview#

Week 1#

Note

You should be able to:

  • Import and store CSV and Excel data

  • Get a data overview and show the dataframe metadata

  • Rename columns

  • Change data types

  • Calculate statistics

  • Select and filter data

  • Save data as CSV and Excel

Week 2#

Note: we will use structured data (i.e. a pandas dataframe and not images) in the exam

Note

You should be able to:

  • Fit a decision tree model using train test split

  • Evaluate a decision tree model

Week 3#

Note

You should be able to:

  • Prepare the data for the model

  • Fit a random forest tree model

  • Obtain feature importance

  • Evaluate the model (interpret accuracy, recall, precision, F1-Score)

Week 4#

Complete the OpenAI-Setup

Not relevant: Use the OpenAI model API to generate images and text

Week 5#

TensorFlow code is not relevant

Week 6#

*optional (not relevant for e-exam):

Note

You should be able to:

  • Choose the right transformers pipeline for a specific use case

  • Interpret the results from your model

Week 7#

Solution

Note

You should be able to:

  • Prepare the data to perform cluster analysis

  • Use the K-Means algorithm

  • Visualize the result with Altair

Week 8#

Solutions

Note

You should be able to:

  • Prepare the data to perform cluster analysis

  • Create a dendrogram

  • Perfrom hierarchical cluster analysis with ward

  • Visualize the result with Altair

Week 13#

Solution

Week 14#

Solution

Week 15#

Solution