Administrivia 🧐

🧠 Introduction to AI (I2AI)

Admin
Author
Organisation

Andy Weeger

Neu-Ulm University of Applied Sciences

Published

February 12, 2024

Modified

May 8, 2024

General remarks

This course will be taught using a blended learning approach.

You need to prepare the content of the individual lectures independently by using the lecture notes and the reading material provided (e.g. references).

The focus of the lessons is on answering your questions, discussing application domains and the exercises.

Please reserve enough time to prepare, reflect, and deepen the contents on your own.

Discussion

What to you expect to learn in this lecture?

Contents

AI is defined here as the study of agents that receive percepts from the environment and perform actions.

In this course, we will

  • cover different types of agents (i.e., goal-based and utility-based agents)
  • illuminate some concepts and major functions they implement,
  • discuss, how to convert these agents into learning agents,
  • identify and discuss real life use cases for these agents, and
  • have a look at philosophical stances and ethical implications of AI.

Learning objectives

During this course, you should advance your skills in the following areas:

  • Understanding of the origins, strengths and limitations of AI
  • Basic knowledge of concepts, functions, and use cases of AI
  • Basic knowledge of problem-solving algorithms, knowledge representation, probabilistic reasoning, machine learning, and natural language processing
  • Capability to apply your knowledge and understanding of AI to different managerial and organizational contexts
  • Ability to assess the potential of AI and use it in digital innovations
  • Ability to evaluate new information and to question existing assumptions
  • Capacity to assess social and ethical implications of AI applications

Supporting literature

This course is essentially based on Russel and Norvig (2022)

Artificial Intelligence: A Modern Approach, Global Edition, 4/E

Russell / Norvig

ISBN-10: 1292401133 • ISBN-13: 9781292401133

The 3rd edition is available in the libary

Exam

There will we a written exam at the end of the semester.

The exam will

  • take place during the examination weeks,
  • will last 90 minutes,
  • cover all contents discussed in lecture,
  • focus on the application of the knowledge gained in the course.

Schedule

It is of importance that you reflect the contents of the session continually, do the exercises and ask questions.

Date Topic Preparation
18.03.2024 Administrivia, Introduction & Agent Types -
25.03.2024 Search Lecture Notes
08.04.2024 Propositional Logics Lecture Notes
15.04.2024 Probabilities Lecture Notes
29.04.2024 Learning Lecture Notes
06.05.2024 Generative AI & Hybrid Intelligence Article1
13.05.2024 Ethics Case Study
03.06.2024 Guest speech: Reality of AI/ML in Industry -
24.06.2024 Final Q&A Questions
Table 1: Schedule summer term 2024 (may be subjected to changes)

Concluding remarks

Why don’t we focus on ChatGPT and the like only?

Because I am convinced that as a Master of Science in Digital Innovation Management you should understand some of the theoretical (mathematical) foundations of AI. However, you should also acquire practical skills on your own, e.g. in interacting with GenAI2.

Literature

Russel, Stuart, and Peter Norvig. 2022. Artificial Intelligence: A Modern Approach. Harlow: Pearson Education.