The course will cover central concepts, methods, techniques, and tools within DataOps and MLOps. Topics include Data Augmentation, Labeling, Cleaning, Pre-processing, Quantifying the Data Quality, Lifecycle, machine learning model deployment, ML pipeline orchestration, monitoring and maintenance (via updating with transfer learning OR retraining) in production, ensemble algorithms, and technical infrastructure. 


Bachelor and master degrees in computer science or software engineering, including knowledge on machine learning and data management as introduced in typical undergraduate courses, as well as significant practical experience with these topics. 

Organizer: Torben Bach Pedersen

Lecturer: Professor Alexandros Nanopoulos, University of Hildesheim

ECTS: 2.0

Time: September 5-7, 2022

Place:  Physical, at Department of Computer Science, AAU, Selma Lagerløfs Vej 300, 9220 Aalborg Ø, room 0.2.90

Number of seats: 15

Deadline: August 15, 2022

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3.000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year.
We look forward to your registrations.