This repo contains datasets, jupyter notebooks and other course material relevant for computer labs of the course Trustworthy AI for Business and Society taught as part of the masters Data Science and Business Analytics at the University of Amsterdam. In case of questions, please send me an email to t.e.rober@uva.nl.
In week 1 we'll solely focus on setting up your machine. Head to 01_intro for a step by step instruction of setting up your machine and the virtual environment.
For each week, starting week 02, there will be a notebook file with exercises to be done and discussed during the tutorial sessions. The solutions will be made available here after the tutorial. There is also a graded assignment about the material of each week. Again, solutions will be published after the submission deadline.
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├── datasets/ # datasets used for tutorials and assignments will be made available here
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├── 01_intro/ # instructions on setting up environment & code for data pre-processing
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├── 02_glassbox/
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├── 03_unboxing/
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├── 04_other_approaches/
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├── 05_federated_learning/
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├── 06_differential_privacy/
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└── README.md