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
Requirements
- Basic knowledge of Python, linear algebra & probability theory