STUDIES

This page offers information about the curriculum, including the courses and their structure, as well as the length, structure, and content of the semesters.

Furthermore, you can find a comprehensive list of completed master's theses since the inception of the program during the academic year 2019-2020.

all classes

Detailed list

According to the decision of the Special Inter-Institutional Committee, next to the title of each course, there are the indications C, P, E, which mean that the course is compulsory, preparatory and elective respectively.

1st semester

Fundamentals and Background on Artificial Intelligence (C, P)

Tutors: S. Konstantopoulos, M. Filippakis, A. Charambidis, G. Vouros

Knowledge Representation and Reasoning (C)

Tutors: S. Konstantopoulos, A. Trompoukis, A. Charambidis

Machine Learning (C)

Tutors: Th. Giannakopoulos, G. Vouros

2nd semester

Natural Language Processing (E)

Tutors: E. Stamatatos

Scalable Artificial Intelligence Methods (E)

Tutors: N. Katzouris, E. Alevizos

Machine Learning οη Multimedia Data (E)

Tutors: Th. Giannakopoulos, I. Maglogiannis

Deep Learning (C)

Tutors: Th. Giannakopoulos, G. Vouros

Artificial Intelligence Applications (C)

Tutors: S. Konstantopoulos, G. Vouros, I. Maglogiannis, M. Halkidi, Ch. Rekatsinas, O. Telelis, M. Filippakis

Robotics (E)

Tutors: M. Dagioglou, G. Stavrinos

3rd semester

Master thesis (C)

Tutors: Supervisors are appointed according to the topic of the thesis.

The duration of the Inter-institutional Master's Program is 18 months. It consists of two semesters of study and one semester for the development of the MSc thesis.

Typically, the courses are held at the premises of the Inst. of Informatics and Telecommunications of NCSR “Demokritos”, usually Monday to Friday from 18:00 to 21:00. However, it is possible to hold additional lectures, presentations or seminars depending on the needs of the study program in NCSR “Demokritos” or in other places.

The MSc accepts applications for study usually in April and May of each year.

The calendar is typically structured as follows:

1st SEMESTER (WINTER)

The 1st semester usually starts in October and ends in January. It includes 1 preparatory and 5 compulsory courses. Each course consists of 13 lectures, while it is possible to schedule courses and presentations according to the needs of each course. After the end of the semester there is an examination period of 2 weeks.

2nd SEMESTER (SPRING)

The Second Semester starts in March and ends in June. It includes 6 courses, two compulsory and four electives. Each course consists of 13 lectures, while it is possible to schedule courses and presentations according to the needs of each course, followed by a 2-week examination period in July.

Students are examined for their knowledge either through written or oral exams, or through the preparation of assignments, or through a combination of the above methods. The method of examination of each course is announced in the first course lecture.

3rD  SEMESTER (WINTER)

The 3rd Semester is devoted to the MSc thesis. This can be completed as part of internship with external partners.

OPERATING REGULATION

The Operating Regulation of the inter-institutional program MSc in Artificial Intelligence is available here.

The Study Guide has been designed to assist you in obtaining a comprehensive understanding of what the MSc in Artificial Intelligence has to provide. Within this guide, you will discover information regarding the program's philosophy and objectives, the course structure and intended outcomes, as well as other useful material to reference throughout your studies.

Study Guide 2023-2024

In 2019, the MSc in Artificial Intelligence welcomed its first cohort of students. Since then, 78 individuals have been admitted to the program and on this page you will find the master's theses of those who have completed their studies to date.

The page is organised as a list, with the names of the students and the titles of their master's theses. By clicking on the titles, you can find more information about the topics and the supervising professors. The papers are grouped by the year in which the students were admitted to the program.

Visit the page to see the full list.