Programming and Implementation#

Python Introduction#

Content:
Interactive introduction to the basics of Python with Jupyter notebooks as well as basics of data processing, -preparation and -visualisation.

Learning Objectives:
The students are familiar with the programming language Python.

Link to the repository:
Check out https://git.rz.tu-bs.de/ifn-public/ki4all/python-introduction or

git clone https://git.rz.tu-bs.de/ifn-public/ki4all/python-introduction

Previous Microcredits: None

Extent: 0.75 ECTS
Responsible: IFN, TU BS

PyTorch and Tensorflow Introduction#

Content:
Use of deep neural networks to solve a multiclass classification problem, familiarisation with recognised academic datasets such as MNIST and CIFAR-10, introduction to the use of the deep learning libraries PyTorch and Tensorflow, use and adaptation of pre-trained models.

Learning Objectives:
The students master the basics of the deep learning libraries PyTorch and Tensorflow. Also they assess the quality of deep learning models on appropriate data sets and with meaningful metrics.

Link to the repository:
Check out https://git.rz.tu-bs.de/ifn-public/ki4all/pytorch-and-tensorflow-introduction or

git clone https://git.rz.tu-bs.de/ifn-public/ki4all/pytorch-and-tensorflow-introduction

Previous Microcredits: None

Extent: 0.75 ECTS
Responsible: IFN, TU BS