Fundamentals of Artificial Intelligence Programme (2024-2025)
Fundamentals of AI Programme (FAIP) is an elective course that is designed to teach master students the basics of Artificial Intelligence (AI). The aim of the course is to describe fundamental concepts and techniques of AI, explain possibilities and limitation of AI systems, and examine technological and ethical perspectives on AI.
This course offers a coherent and broad introduction to AI and a small project with the aim to apply AI solutions to a real world problem proposed and supervised by researchers from the TU Delft AI Labs [link: https://www.tudelft.nl/ai/tu-delft-ai-labs ]. This is one whole 15EC course that consists of course work and a project where you develop an AI solution and apply your knowledge. Available projects will be announced starting in June.
You will be offered a broad introduction to topics such as: Data engineering, Ethics in AI, Machine Learning, Unsupervised Learning, Neural Networks, Natural Language Processing, Computer vision, Robotics.
The setup of this AI elective consists of a blended design whereby the flipped classroom approach is used. Students are offered online video lectures, papers, quizzes to prepare themselves. The day after they have an on-campus session with teaching staff where they dive deeper in the material collectively.
This course aims at MSc students from all faculties of TU Delft with no to little prior AI knowledge and those that want to explore the field of AI within their own domain. For example, an architecture student that wants to improve their AI knowledge to formulate an AI solution within the architecture domain.
- Prerequisite knowledge: basic programming skills and basic knowledge of statistics. Knowledge of linear algebra is a plus.
- This course is not accessible for computer science and robotics students because it has too much overlap with their programmes.
Information academic year 2024-2025:
15EC course
Start date: 2 September – 8 November 2024 (during Q1)
Application Procedure: you can now enroll through Project Forum and indicate your preference for a project.
Enroll here: https://projectforum.tudelft.nl/course_editions/108
Teaching staff
Seyran Khademi
ABE, AiDAPT Lab
Responsible lecturer and course coordinator
Computer vision
Arkady Zgonnikov
ME, HERALD Lab
Project coordinator
Myrthe Tielman
EEMCS, AI*MAN Lab
Introduction to AI, MAS
Emir Demirović
EEMCS, XAIT Lab
Data Engineering
Jazmin Zatarain Salazar
TPM, HIPPO Lab
Ethics in AI
Christoph Lofi
EEMCS
DBMS
Ujwal Gadiraju
EEMCS, Design@Scale Lab
Data work, Interpretable & explainable AI
Jie Yang
EEMCS, Design@Scale Lab
Data work, Interpretable & explainable AI, NLP
Avishek Anand
EEMCS
NLP
Junzi Sun
AE
Combinatorial Optimisation
Stefan Buijsman
TPM
Multi objective decision support & Ethics in AI
Juan Manuel Duran
TPM
Multi objective decision support & Ethics in AI
Tom Viering
EEMCS
Machine Learning
Hanne Kekkonen
EEMCS, SLIMM Lab
Regularization
Alexander Heinlein
EEMCS
Ranking for recommender systems
Alfredo Nunez Vicenco
CEG
Unsupervised Learning
Hongrui Wang
CEG, Faculty member TU Delft AI Labs
Unsupervised Learning
Wendelin Böhmer
EEMCS, BIOLab
Reinforcement learning
Luca Laurenti
ME, HERALD Lab
Neural Networks
Amira Elnouty
EEMCS
Dimensionality reduction
Martin Klomp
ME
Robotics
Pierre Mercuriali
ME
Symbolic AI & Knowledge Representation
Ibo van der Poel
TPM