Artificial Intelligence: Modern Methods (16-27 Aug.)

Goals of the course: The students will achieve working knowledge and hands on experience with the modern methods of the fast growing field of artificial intelligence.

The module will cover the following topics:

• What does the Deep-Learning-revolution mean for science and industry?
• Which methods of machine learning exist and their relative pros and cons?
• For which user cases is the application of these methods useful?
• How do I build and train a neural network for a given problem?
• Different types of neural networks (CNN, RNN, …)
• Generative modelling (AE, VAE, GAN, …)
• Healthy scepticism: evaluation of performance and accuracy.
• Discussion on ethics and privacy of data.

 Roadmap: 

Statistical Analysis, Optimization, Machine learning , Neural Networks, Deep Learning, Tensorflow and Keras, Applications, Own project.