Are you familiar with Python, Linear Algebra, and Probability Theory? However, you would like to delve deeper into them? From 09-10 December, you will learn how to apply and use Deep Learning to solve problems in the 2-day workshop ‘AI Deep Dive’. The course takes place in cooperation with the Graz University of Technology.

Course contents:


Day 1

  • How do neural networks learn?
  • Mathematical understanding of feed-forward networks
  • PyTorch Basics
  • Data processing in PyTorch
  • Train and evaluate feed forward networks
  • Understanding common problems in neural networks
  • Transfer PyTorch to PyTorch-Lightning
  • Table-based data modeling with neural networks


Day 2

  • Convolutional Neural Networks (CNN) & understand the common architectures
  • Image Classification with CNN and Transfer Learning
  • Sequence modeling of time series
  • Tips and tricks for the modeling of neural networks
  • Overview of advanced neural network architectures



The course is aimed at:

  • Experts, e.g. IT employees, team leaders, project managers, process owners, innovation managers
  • Software developers and data engineers
  • Data Scientists


  • Basic knowledge of Python, linear algebra & probability theory


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