Engineering with AI


Ultimately, one of the TU Delft’s objectives is that all students at TU Delft should be exposed to AI (Artificial Intelligence) education. That is why the TU Delft has recently launched 24 Delft AI Labs. Each faculty has now several AI labs, that aim to combine AI research with topics of interest from the faculty. For example, the faculty of Aerospace Engineering is investigating the use of graph neural networks to predict air traffic delays in a network of interconnected airports.

To stimulate students to combine AI with topics of their faculty, this new minor programme (Engineering with AI) was launched in the academic year 2021-2022. This was a pilot launch; you can read more about it in this news article. In the academic year 2022-2023, we will enter the second iteration of the pilot.

Students that complete this minor programme will - in their MSc programme of their faculty - gain access to the 15 EC course “Interdisciplinary Advanced Artificial Intelligence Project” (see TU Delft study guide). Together, this minor and this MSc course will allow you to do a MSc thesis project that combines AI with topics of interest of your faculty.

Furthermore, it is highly likely you will encounter AI techniques in your job after your studies. In this minor you will learn how to use AI techniques such as neural networks. At the end of the minor programme you will work together with an expert researcher from your faculty or one of the Delft AI Labs. Together with them you will develop or investigate an AI solution as part of the “Capstone Applied AI” project.

In this minor program you will also learn how AI and machine learning algorithms work and how you can apply them the right way. You will also learn the pros and cons of AI techniques, their limitations and possible associated ethical problems. You will get to know all the ins and outs of AI; you will be able to tune settings or to use specific AI algorithms using toolboxes, and will learn what is ‘under the hood’ of the AI toolkit.

By the end of this minor you will:

  • know how to apply AI techniques in your specific study field,
  • how to reformulate problems of your field such that they can be solved by AI algorithms,
  • recognize the limits and failures of AI solutions and know how to try and fix them.

For whom?

All BSc students from TU Delft except Computer Science BSc students can enrol for this minor. If you do a double BSc degree that includes computer science (for example: math and computer science) you are also not allowed to take this minor.

Who cannot attend?

  • Computer Science BSc students
  • Double BSc degree students with Computer Science (such as math and CS),
  • HBO students,
  • Students outside of TU Delft.

Information for bachelor’s students from Applied Mathematics (BSc TW):

The following course replacements are required for the BSc Technische Wiskunde (TW) students.

Engineering with AI Minor (TI-Mi-225) course: The content equivalent for BSc TW students: To be replaced by:
Introduction to Python Programming
Introduction to Programming
Big data Processing
Algorithms & Data Structures
Algorithms & Data Structures
Computer Organisation


In order to be able to successfully start this minor, you need to have some basic programming skills. To help you figure out whether you are at the correct level, we have created a mini-course on Python Prerequisites. You can find our mini-course here: Please check it out before registering for this minor programme. If you have trouble doing the assignments, this minor programme might not be for you.

In addition to basic programming skills, knowledge of university-level mathematics (calculus, linear algebra, probability, and statistics) is recommended. Especially for students from IDE / IO and BK / A+BE, self-study in the summer is required (15-20h), because not all linear algebra and statistics is covered in the BSc programme. You can find a detailed description of the self-study material here:

What will you learn

The main learning objectives are as follows, split per three core pillars:

  • Computational thinking
    The student will be able to explain the basic concepts of computational thinking, describe how algorithms operate on data, and discuss the differences in the complexity of algorithms.
  • Artificial Intelligence
    The student will be able to describe the fundamental concepts and techniques of AI, explain the possibilities and limitations of AI systems and the importance of their validation, and can apply at least one AI technique or analyse an AI application area, preferably in the field of their major.
  • Societal impact
    The student will be able to examine the technological, societal and regulatory perspectives on AI, assess the impact of deploying AI-based solutions and interventions on individuals, organizations and society, and apply ethical considerations in the design of its own AI system in the field of his/her major.

Course overview

Below is a short description of all courses. For more information, please see the studyguide.

Quarter 1

[TI3105TU] Introduction to Python Programming

The course aims at achieving a programming level that is needed to be able to implement AI algorithms. You will be able to work with external libraries, which can also be applied to the use of popular AI packages used by academia and industry.

[TI3145TU] Introduction to Machine Learning

The course aims at learning the basic concepts underlying machine learning techniques and applying and fine-tuning Python machine learning algorithms on various datasets.

[TI3111TU] Algorithms and Data Structures

The course aims at providing foundational knowledge of computer science concepts required in programming AI algorithms and manipulating AI data structures.

Quarter 2

[TI3140TU] Introduction to AI and Engineering Responsible AI

The course aims at explaining the most common views on what AI is. You will be able to examine the technological, societal and regulatory perspectives on AI and assess the impact of deploying AI-based solutions and interventions on individuals, organisations, and society.

[TI3150TU] Capstone Applied AI project

In this course, you will apply the topics learned in the previous minor courses on a group project with regards to your field of study. The project will be supervised by faculty staff and PhD students from the major field of study of your major.

Education methods

The courses will be taught on campus. In Q2 there are multiple mandatory on-campus activities, in Q1 only the exams are mandatory on campus activities.

The courses in Q1 do not have mandatory lectures or lab sessions; these are all optional to help you master the material. “Introduction to Python Programming” and “Algorithms and Data Structures” feature an on-campus exam, where you have to take the exam with programming exercises on a computer. “Introduction to Machine Learning” exam is a course with a mandatory AI project that is executed in pairs - graded using a report in addition to an on-campus “pen and paper” exam.

In Q2 “Introduction to AI and Engineering Responsible AI” has a few mandatory activities on campus, and is graded based on a written paper. “Capstone Applied AI” project features group work and mandatory meetings with your supervisors, teaching assistants and your student group (with +/- 5 students per group). The “Capstone Applied AI” has a mandatory on-campus midterm presentation and final presentation; the project is also graded using a report.


Register for this minor

To register, please follow the procedure described at Minors - English page, or Minors- Dutch page.

Frequently asked questions

Can I follow this minor if I am an MSc student?

No, the CS minor is only for BSc students.

Can I follow this minor If I am not a student from TU Delft?

No, only BSc students from TU Delft can participate excluding BSc Computer science students.

Can I replace the course on Python programming?

Some students have already done a course on Python in their bachelor’s programmes and wonder whether they can get a replacement for the Python course in this minor programme (TI3105TU). Our answer: we cannot offer a replacement for TI3105TU, unless you are a Mathematics student from the TU Delft (in which case you should follow the replacement table presented above).

I did a programming course (or other course) at faculty XYZ, can I replace a course in the minor programme by this course?


Engineering with AI minor coordinators