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Introduction to Artificial Intelligence

Winter school: January 6th to 31st, 2020

Course price: 1,950 Euros

18 hours of class sessions per week, 5 ECTS credit points

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Topic

Introduction to Artificial Intelligence

Target group

Bachelor, Master, and Doctoral students with a technical background and interest in artificial intelligence.

Learning Goals

The primary goal of this course is that students gain an understanding of some of the fundamental methods and algorithms of AI, and an appreciation of how they can be applied to interesting practical problems, via a number of toy examples. The secondary goal of the course is that students learn how to conduct independently research, developing solutions to simple project tasks.

Course Components

This course has three components: lecture, tutorial and project classes. The lectures will introduce selected basic topics such as search, game playing, decision making, planning, machine learning and probabilistic reasoning and resource allocation (i.e. social choice). The tutorials will allow students to apply algorithms on simple "toy" examples. The projects will provide to the students the opportunity to develop a small solution in some area of AI: social choice, fair division, learning, planning, theorem proving, etc.

Short Description

Artificial Intelligence (AI) is about creating algorithms to perform tasks in a way that we believe is intelligent. AI is about creating algorithms to make robots perform such tasks. Modern AI algorithms play games (e.g. chess), prove theorems (e.g. verification), discover patterns in data (e.g. explanations), analyze complex sequences (e.g. DNA), make ``life or death’’ decisions (e.g. matching organs to patients), optimize distributions (e.g. food, refugees, housings), drive cars (e.g. Tesla), play soccer, etc. 

Students who complete the course will have an understanding of some of the fundamental methods and algorithms of AI, and an appreciation of how they can be applied to interesting practical problems.

Prerequisites

The general prerequisites of the TU Berlin Summer & Winter University are that candidates have B2 level English and at least one year of university experience.

In addition, the following requirements are mandatory for this course:

1. Basic programming skills: C++ or Java or PHP or Prolog (advanced programming skills are not necessary, whereas eagerness for learning a new programming language is necessary)

2. Basic LaTeX (a type setting system) and Word skills

3. Knowledge: basic AI algorithms, mathematics.

4. Eagerness to learn new programming tools.

Lecturers

Dr. Martin  Aleksandrov

Martin Aleksandrov obtained a Bachelor degree in Computer Science from Sofia University, Bulgaria. He also received a Master degree in Computer Science from Technical University Dresden, Germany. In addition, Martin obtained qualifications as Bachelor in Physics and Master in Probability Theory and Statistics from Sofia University, Bulgaria. He recently received his PhD in Computer Science from UNSW Sydney, Australia. Martin was an intern at Fondazione Bruno-Kessler (FBK in Trento, Italy) and Australian ICT Research Centre of Excellence (fka NICTA in Sydney, Australia). He also worked at NOVALINCS (fka CENTRIA in Lisbon, Portugal). He has won Computational Sustainability Outstanding Student Paper Award at 24th IJCAI 2015, Buenos Aires, Argentina, and Best Paper Award at 40th KI 2017, Dortmund, Germany.

Schedule and Syllabus

You can find the syllabus for this course HERE. 

The "Berlin/Culture" time slots are reserved for the cultural activities included in the tuition fee, as well as for the additional tours and trips that we offer.

These activities are of course completely optional, should you want to use the time to explore the city by yourself, catch up on homework, or relax. You may find the syllabus useful when discussing with your home University whether the ECTS credits attainable for this course are accepted by them.

Winter school: January 6th to 31st, 2020

Course price: 1,950 Euros

18 hours of class sessions per week, 5 ECTS credit points

Zusatzinformationen / Extras

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Contact

Beth Sibly, Director
+49 30 4472 0230