TECHNICAL UNIVERSITY OF DENMARK · DENMARK
Machine Learning Operations
Master's · Taught in en
At a glance
3 mo
Duration
—
IELTS
€15k
Tuition / yr
en
Language
Master's
Level
- 3 weeksCourse Duration
- EnglishLanguage of Instruction
- Campus LyngbyLocation
- Group ProjectProject Work
- EuroTeQ Virtual Mobility CourseCourse Type
This course focuses on Machine Learning Operations (MLOps), providing students with practical skills and knowledge to manage machine learning models in research or production environments. You will learn about essential tools and software development practices for organizing, scaling, deploying, and monitoring ML models. The course emphasizes hands-on experience with various frameworks, both local and cloud-based, to build and manage large-scale machine learning pipelines. The curriculum covers crucial aspects like code organization, version control, reproducible environments, experiment management, debugging, profiling, and monitoring. You will also gain experience with testing, continuous integration, and cloud infrastructure for scaling experiments and automating processes. The course aims to equip students with the ability to deploy ML models effectively, monitor their lifecycle, and scale data loading and training using distributed frameworks.
Curriculum
The course includes lectures, exercises, and project work. Lectures provide context for each topic, while the main focus is on practical tools and coding skills for production ML. Approximately 30% of the course is dedicated to group project work.
- 2025/2026
- Machine Learning Operations02476
Frequently asked questions
- What are the tuition fees for this programme?
- International students are required to pay 7500 EUR per semester. The total tuition fee for two years of MSc studies is 30000 EUR. Please note that tuition fees are subject to revision for the Autumn 2026 intake.
- What is the duration of this programme?
- The programme is listed with a course duration of 3 weeks. This appears to be a short course, possibly a virtual mobility course, rather than a full Master's degree programme.
- What are the entry requirements for this course?
- Applicants should have a general understanding of machine learning and basic knowledge of deep learning. Familiarity with coding in Pytorch is required, and completion of Course 02456 is recommended.
- How do I apply for this course?
- You must be enrolled in a degree program at a partner university or have an exchange agreement with DTU. Your home institution must nominate you, and you should submit your application through your home university's international office. Specific deadlines should be confirmed with your home university.
- What is the language of instruction for this course?
- The language of instruction for this course is English.
- What career opportunities does this programme offer?
- The skills gained are applicable to organizing, scaling, deploying, and monitoring machine learning models in research and production settings.
Entry requirements
PrerequisitesGeneral understanding of machine learning (datasets, probability, classifiers, overfitting etc.) and basic knowledge about deep learning (backpropagation, convolutional neural networks, auto-encoders etc.). Familiarity with coding in Pytorch is required. Course 02456 is recommended.
This course is offered as a single course and is part of the MSc programmes in Autonomous Systems and Human-Centered Artificial Intelligence.
Fees
Tuition (international)7500 EUR per semester. Total for 2 years of MSc studies is 30000 EUR.
Tuition (home)EU/EEA citizens are not required to pay tuition fees.
Living—
Tuition fees are expected to be revised for the Autumn 2026 intake. Please check the university website for the latest information.
How to apply
1. Check Eligibility and AgreementVerify if your home university has an exchange agreement with DTU. If you are applying through Erasmus+, consult your home university's Erasmus coordinator. Ensure you meet the minimum academic requirements (e.g., completed first two years of study).
2. Get Nominated by Home InstitutionYour home institution must nominate you before you can submit your application to DTU. DTU does not accept applications from 'free movers' unless through a formal exchange agreement.
3. Submit ApplicationFinal admission decisions are made by DTU after reviewing your application materials. Specific application procedures and deadlines should be obtained from your home university's international office.
4. Sign Up for the CourseRegistration for individual courses is done through the Study Planner on the DTU website.
Frequently asked questions
What are the tuition fees for this programme?
+
International students are required to pay 7500 EUR per semester. The total tuition fee for two years of MSc studies is 30000 EUR. Please note that tuition fees are subject to revision for the Autumn 2026 intake.
What is the duration of this programme?
+
The programme is listed with a course duration of 3 weeks. This appears to be a short course, possibly a virtual mobility course, rather than a full Master's degree programme.
What are the entry requirements for this course?
+
Applicants should have a general understanding of machine learning and basic knowledge of deep learning. Familiarity with coding in Pytorch is required, and completion of Course 02456 is recommended.
How do I apply for this course?
+
You must be enrolled in a degree program at a partner university or have an exchange agreement with DTU. Your home institution must nominate you, and you should submit your application through your home university's international office. Specific deadlines should be confirmed with your home university.
What is the language of instruction for this course?
+
The language of instruction for this course is English.
What career opportunities does this programme offer?
+
The skills gained are applicable to organizing, scaling, deploying, and monitoring machine learning models in research and production settings.