02901 Advanced Topics in Machine Learning: Machine Learning Operations MLOps

August 18-22, 2025

Description

The course consists of five days of lectures, exercises, a hackaton, and presentations. The lectures will cover theoretical and practical aspects of Machine Learning Operations. Technical aspects, programming and application of the covered concepts will be explored in tutorials and exercises. The course (2.5 ECTS points) is passed by participating and presenting the work done in the hackathon. For further course details click here.

Location

Technical University of Denmark, Building 308, Lecture hall 001. (Address: Richard Petersens Plads 308, 2800 Kgs. Lyngby, Denmark)

Preliminary Course Programme

Monday (9 - 16):

Nicki Skafte Detlefsen, Associate Professor at DTU Compute, Introduction to Machine Learning Operations.
Nicki Skafte Detlefsen,, MLOps and Orchestration

Tuesday (9 - 16):

Iacopo Colonnelli , Assistant Professor at Computer Science Dept., University of Torino, Italy, Federated Learning
Raghavendra Selvan, Assistant Professor at Dept. of Computer Science, University of Copenhagen, Resource Efficient Machine Learning
Summer School Dinner at 18

Wednesday (9 - 16):

Emil Njor, Postdoc, and Riccardo Miccini, Industrial PhD, at DTU Compute, Section for Embedded Systems Engineering, Embedded Systems and SBC
Sebastian Topalian, Research Scientist at Novonesis, ML in Production

Thursday (9 - 20):

The hackathon takes place at DTU Skylab, room 101A (Auditorium). (Address: Diplomvej 373D, 2800 Kongens Lyngby, Denmark)

(9-10) Introduction to Hackathon
(10-20) Hackathon with MLOps and Embedded AI

Friday (10 - 16):

(10-12) Hackathon finalized
(13-16) Group presentations and Exam. Taking place in building 321, room 119 and 227 (see DTU Learn for exam schedule)

Requirements

General understanding of machine learning, statistical modeling, mathematics and computer science. Programming experience, ideally in Python. For the course you are required to bring your own laptop computer.

Application and Registration

To participate in the course, an application is required. The application deadline has passed an there are no more open spaces for this years course.

After receiving a positive confirmation on the application, registration in DTUs systems must be carried out. For academics (masters and PhD students) there is no registration fee for the course. Students affiliated with DTU can use the course planner to register. PhD students outside of DTU have register via here. For all other participants a course fee will be charged and apart from signing up additional registration must be completed here.