Bachelor, Master, and Doctoral students with a technical background and interest in artificial intelligence.
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.
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.
Artificial Intelligence (AI) is about creating algorithms to perform tasks in a way that we believe is intelligent. 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.
Many of these AI applications use a number of introductory algorithms and techniques, some of which are covered in the course. Examples of such preliminary methods are Depth-First Search, Breadth-First Search, Minimax Search, Tree Pruning, Backtracking Search, Simulated Annealing, Graph Plan, Decision Tree Learning and Perceptron Learning. Thus, students who complete the course will have an understanding of some of the fundamental methods and basic algorithms of AI.
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 skills: C++ or Java or PHP or Prolog
2. Basic skills: LaTeX (a type setting system) or Word skills
3. Knowledge: some of the basic AI algorithms, mathematics.
4. Eagerness to learn new programming tools.
5. Eagerness to learn new abstract algorithms.
Students with elementary knowledge in AI and mathematics are strongly encouraged to apply. In order to decide their eligibility, students are welcomed to check out the course syllabus for a more detailed description of the course components. Accepted students are also encouraged to ask questions and be active in classes.
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.
Please direct questions about the course to the TU Berlin Summer University Team at: email@example.com . We will answer your questions and direct specific queries regarding course content to the course lecturers where necessary.
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.