Artificial Intelligence (AI): Modern Methods
This module takes place online.
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.
Programme – The course is taught in English (4 ECTS)
Requirements – Knowledge of advanced mathematics (calculus, statistics); at least one programming language (Python, Java, C++ or similar); at least 2 years of undergraduate studies or enrolment in master studies; topics of study: computer sciences, engineering, physics, mathematics, chemistry, biology or materials
Programme fee – EUR 500.00
Application deadline – n/a
If you are a student from the University of Massachusetts system, the University of Wisconsin system, and participating universities in Queensland you will participate as exchange students and will not pay fees directly to Frankfurt Digital Summer School. Please contact your study abroad advisor for more information on how and when to apply.
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.
Statistical Analysis, Optimization, Machine learning , Neural Networks, Deep Learning, Tensorflow and Keras, Applications, Own project.