Postgraduate Diploma Thesis

Skills Development

Knowledge Deepening / Consolidation

The course is also offered to exchange programme students.

1) In-depth Knowledge Acquisition. Students demonstrate a comprehensive understanding of the chosen research topic, including relevant theories, methodologies, and existing literature. 2) Critical Analysis and Evaluation. Students develop the ability to critically analyze and evaluate existing research, identifying gaps and limitations in the current literature. 3) Research Design and Methodology. Students design and implement appropriate research methodologies, demonstrating a mastery of both qualitative and/or quantitative research techniques. 4) Data Collection and Analysis. Effectively collect, manage, and analyze data using appropriate tools and techniques, drawing valid conclusions and insights from the findings. 5) Independent Research and Problem-Solving. Students demonstrate the ability to work independently, showing initiative in identifying and solving research problems encountered during the course of the thesis work. 6) Contribution to Knowledge. Students make an original contribution to the field of Artficial Intelligence by providing new insights, perspectives, or solutions that extend the current body of knowledge. 7) Communication and Presentation Skills. Students communicate research findings clearly and persuasively in both written and oral forms, demonstrating proficiency in academic writing and presentation skills.

The master's thesis in Artificial Intelligence delves into the forefront of AI research, addressing contemporary challenges and pushing the boundaries of technological innovation. Students engage in original and impactful research projects, exploring diverse aspects of AI such as machine learning, deep learning, natural language processing, and computer vision. The thesis work encompasses both theoretical and practical dimensions, allowing students to apply sophisticated algorithms to real-world problems. Leveraging advanced methodologies and state-of-the-art tools, the research investigates novel solutions that contribute to the evolving landscape of AI applications. Emphasizing interdisciplinary collaboration, the master's thesis encourages students to integrate AI technologies with other domains, fostering a holistic approach to problem-solving. The culmination of this thesis represents a significant contribution to the field, showcasing the student's expertise in AI and their ability to make meaningful advancements in this dynamic and rapidly evolving field.

Computational Vision, Computational Intelligence- Statistical Learning, Statistical Signal Processing- Time Series, Biosignal Analysis- Neuroinformatics, Games and Artificial Intelligence, Complex Systems: From the society to the web, Bioinformatics and Digital Biology, Deep Learning and Multimedia Information Analysis, Autonomous Systems Perception, Signal Processing for Brain Interfaces, Virtual Reality, Language Technology

03-12-2023