Organisation
| Time | Monday, 8:15h-11:30h |
|---|---|
| Room | 120 |
| E-Learning | Course in Ilias |
| Credits | 4 SWS / 6 ECTS |
| Exam | written, 60min |
Announcements
- First lesson in WS 23-24: 19.10.2023
Artificial Intelligence
Maybe you know Artificial Intelligence (AI) from Sci-Fi movies? With intelligent machines that are far superior to humans?
If you expect something like this, you might be on the wrong path. First because AI is not only fictitious and future stuff. It is already pervasive in our everyday life. AI is at the heart of weather forecasts, digital assistents (Amazon Echo, Siri, Google Now, chatGPT), recommendation systems, web-search, fraud detection, face recognition, medical- and technical diagnosis, computer games and much more. Even though we have lots of intelligent machines and applications and AI is supposed to bring major shifts in society, you should not be afraid: AI will not reach the full breadth of human intelligence soon. Intuition, emotions, common sense and social skills are only a few factors of intelligence, which make humans superior.
The message is: AI is something practical. It builds rational agents and it provides a toolbox, which enables new and improves existing applications. This lecture provides a structured entry into AI. The elements of the AI-toolbox are algorithms and datastructures. The mathematical and technical features of these algorithms and their application fields are in the focus of this lecture. On an abstract level AI, as covered in this lecture, can be partitioned into the 4 areas depicted in the figure below. By far the most relevant category is Machine Learning. Therefore, the main part of this lecture is dedicated to this subject.
Jupyterbook and Gitlab Repo of this lecture
Jupyterbook of lecture contents: Click on the card Artificial Intelligence on page https://lectures.mi.hdm-stuttgart.de and ask the instructor for the credentials.
Exercises and further materials
| Exercise | Contents |
|---|---|
| Exercise 1 | Search, Plan, Optimize |
| Exercise 2 | Probability, Uncertainty, Bayes Net |
| Exercise 3 | Entropy, Information Gain, Decision Trees |
| Exercise 4 | Single Layer Perceptron (SLP) |
Literature:
Artificial Intelligence: A Modern Approach (4th Edition) (May, 1st, 2021) by Stuart Russell, Peter Norvig
-
Grundkurs Künstliche Intelligenz (September, 16th, 2016) by Wolfgang Ertel
-
Introduction to Machine Learning (Adaptive Computation and Machine Learning) (01 October 2004) by Ethem Alpaydin
-
Programming collective intelligence : building smart web 2.0 applications (23 August 2007) by Toby Segaran