Artificial Intelligence has made its way into our everyday language and news cycles. Yet, it is still hard to define what exactly an AI is. In this course, you will learn why. We will focus on several techniques associated with AI and give you an understanding of how they work and which kinds of problems they can solve. You will learn Planning, Optimization, Reasoning and Machine Learning. We will visit each of these fields based on practical tasks using the programming language Python.

Learning Goals

By the end of the course students will know

• What Artificial Intelligence is and why it’s hard to come up with an exact definition
• What state space search is and how to select an appropriate Planning or Optimization algorithm
• How to represent and reason about the truthfulness of information programmatically
• How to derive statistical relations from a corpus of information using Data Science and Machine Learning
• To identify which field of AI is a promising approach to solve a given problem
• How to select and implement algorithms from all fields of AI using Python libraries

Course Structure:

The course will contain a combination of learning material (input slides and videos, programming tasks, and quizzes) and will focus on discussing individual questions, solutions and issues.

The course will be accompanied by a sequence of practical programming tasks that build on each other. The current plan is to work iteratively towards one cohesive project via multiple consecutive tasks. This may change slightly if didactic reasons require it. For example, it is possible that different fields of AI will be covered with different projects, if this reduces the overall programmatic complexity of solving the tasks for beginners.

Syllabus:

A detailed syllabus with information on the schedule will be made available to registered participants.
You may find the syllabus useful when discussing with your home university whether the ECTS credits attainable for this course are accepted by them. Please note this is a full-time, intensive course and participants will be expected to attend lectures (18 hours of class per week) and complete independent study Monday through Friday. Additional study may also be required on weekends.The activities of the cultural program are also shown in the syllabus.

The course is directed at intermediate beginners in Software Engineering and Computer Science.

Participants of the TU Berlin Summer & Winter University must meet the following requirements: (i) B2 level English, or equivalent and (ii) at least one year of university experience. Working professionals are also welcome to take part in the program.

The course is directed at intermediate beginners in Software Engineering and Computer Science. It requires previous knowledge in Python, but you don’t need to be an expert. If you know the common programming concepts and can use them to solve low to mid-complexity programming tasks on your own, you should be fine. AI contains a lot of mathematics, but the course is designed to be understandable with the knowledge conveyed in a High School education.

Fluency in Python 3 programming and tools.

Participants are required to bring a fully functional programming device (laptop preferred).

Dr. Frank Trollmann studied at the TU Berlin and has worked in several AI related research projects at DAI-Labor (TU Berlin). After finishing his PhD he became the coordinator of the research group on Self-Adaptive Systems. Since 2019, he has been part of CODE University of Applied Science, a fresh institution that is trying to disrupt education with a project-based learning approach. At CODE Frank Trollmann is responsible for teaching Python to beginners and organizing CODEs AI curriculum. 

Course fees for Introduction to Artificial Intelligence are as follows:

Student: 1950 Euro

Working professional/Non-student: 2340 Euro

The early bird discount is available for all participants until March 1^st 2022.

Please note that students will be required to upload proof of their student status (student card/ enrollment information) during the registration process.