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Master
Machine Learning

Unlock the power of data with Machine Learning! Master cutting-edge technologies from the comfort of your own home.

Online Studies
QS Stars
WES
FIBAA
AACSB
CHE
Wissenschaftsrat
UNESCO

End 2024 right: invest in your career

Apply by January 5th and get a discount of up to €1,444!

Commit to improving your future today and make 2025 your year. Join us on campus in Berlin, study in English, and graduate with an internationally recognised degree. 

Apply Now

End 2024 right: invest in your career

Apply by January 5th and get a discount of up to €1,444!

Commit to improving your future today and make 2025 your year. Join us on campus in Berlin, study in English, and graduate with an internationally recognised degree. 

Apply Now
Overview

Start your Master in Machine Learning

At IU, our online MSc Machine Learning programme equips you with indispensable skills and knowledge to excel in today’s evolving tech landscape.

Pursuing an online masters in Machine Learning at IU allows you to:

  • Study online from anywhere in the world.
  • Balance your studies with your personal and professional life.
  • Gain expertise in advanced machine learning techniques.
  • Collaborate and network with a diverse, global cohort.

In our online MSc Machine Learning programme, you’ll develop the following soft skills:

  • Analytical Thinking 
  • Problem-Solving
  • Adaptability
  • Ethical Awareness  

… and the following hard skills:

  • Programming with Python
  • Deep Learning
  • Big Data Technologies
  • Data Modelling and Reporting 

Your onlinecampus degree summed up

All the facts and figures about your study programme at a glance
OnlineCampus Study Model Degree
Master of Science (M.Sc.)
120 ECTS credits

Language
English
Accreditation & Recognition
Accreditation
Accredited in line with German and European standards


Recognition
Your degree is Internationally recognised and can easily be transferred to another country
Tuition Fees & Discounts
Tuition Fees
Starting from € 299 (US$ 316)* per month
*based on the exchange rate from 30.11.2024 12:00 AM (CET)

Online application
No application fees
Study Duration
Study start
any time

Duration
24 - 48 months (depending on time model)
100 % flexible

You decide where and when you want to study

Modernised learning

Access our unique learning app and AI tutor 

Award-winning education

First-class learning: 96% recommended 

Study contents

Online course overview

Our online MSc Machine Learning programme is meticulously structured to help you gain expertise to excel in the machine learning field. You'll gain both theoretical knowledge and hands-on experience, making you ready for the workforce.

You'll master essential skills such as:

  • Advanced mathematical concepts and statistical analysis.
  • Cutting-edge machine learning methods.
  • Proficient use of machine learning libraries and tools.
  • Ethical and legal considerations in technology.

Here’s a snapshot of your learning journey over four semesters:

Semester 1

ModuleECTS credits

Programming with Python

5

Advanced Mathematics

5

Machine Learning

5

Advanced Statistics

5

Deep Learning

5

Project: Machine Learning Libraries

5

You'll start with foundational technical skills and build up to sophisticated machine learning methods. From Python programming to deep learning, you’ll set a solid base for your career.

Semester 2

ModuleECTS credits

Advanced Research Methods

5

Big Data Technologies

5

Data Modeling and Reporting

5

Seminar: Sustainable, Ethics, and Law in Machine Learning

5

Elective A*

5

Elective A*

5

Delve deeper into research methods and big data while exploring ethical issues in technology. Electives will help tailor your study to your career aspirations.

Semester 3

ModuleECTS credits

Elective B*

5

Elective B*

5

Elective C*

20

This semester elevates your expertise in specialised areas, preparing you for leadership roles in your field.

Semester 4

ModuleECTS credits

Master Thesis

30

Your final semester is dedicated to your Master Thesis, allowing you to delve deep into a specialised topic, demonstrating all the skills and knowledge you've acquired throughout the programme.

Electives overview

Elective A (Choose based on your major):

In your 2nd semester, you'll need to choose two elective modules, which you can choose from the following modules:

Module

ECTS credits

NLP and LLM

5

Natural Language Processing

5

Reinforcement Learning

5

Image Processing and Low Level Vision

5

Corporate Governance of IT, Compliance, and Law

5

International IT Law

5

Data Query Languages

5

Business Intelligence I

5

Case Study: Model Engineering

5

Explainable and Interpretable Machine Learning Models

5

Elective B (Choose based on your major):

In your 3th semester, you'll need to choose an elective module, which you can choose from one of the following modules:

Module

ECTS credits

Voice Assistants

5

Project: Prompt Engineering

5

Mid-Level Vision and Video

5

Computer Vision for Autonomous Systems

5

Seminar: Legal Framework for IT-Security

5

Cyber Security and Data Protection

5

Extract, Transform and Load Technologies

5

Project: Extract, Transform and Load Technologies

5

DevOps

5

Project: Machine Learning Model Building

5

Aditional Electives:

Module

ECTS credits

Artificial Intelligence

5

Project: AI Excellence with Creative Prompting Techniques

5

Elective C - If you decide to do the internship:

Module

ECTS credits

Internship: Master AI, Machine Learning and Data Science

20

Elective C - If you decide to take the three modules instead of the internship:

Module

ECTS credits

Business Communication and Storytelling

5

Design, Lean and Game: Social and Creative Methods

5

Start Up Lab

10

Module guide

Module guide

Course schedule

Online course schedule

All the support you need, any time of day

With this programme, you’ll have access to human and AI-powered tutoring. 

Your tutors will be available to answer any questions, and you’ll have recurring appointments where you can discuss course topics with them and other students. 

Syntea, IU’s AI-powered tutor, will be available 24/7 to guide you through your courses and prepare you for exams. 

Study your way, and master working with AI at the same time. 

Admission

Entry requirements

You can start your desired study programme at IU International University of Applied Sciences if you meet the requirements. 

The admissions documents must be provided in English or German, if they were not issued in one of these two languages, a translation is required. If you need to translate your documents, we can help refer you to our trusted translation partners. You can find more details here. 

General admission requirements

  • Completed, undergraduate degree with 180 ECTS with a STEM (Science, Technology, Engineering, Mathematics) focus.
  • Your degree must be from a state or state-recognised higher education institution/university  
  • You must have achieved a final grade of at least “satisfactory” or Grade C equivalent to the German grade “befriedigend” in your previous undergraduate degree 


Alternatives to the minimum grade (120 ECTS credits) 

If you have completed your bachelor's degree with a grade of "sufficient" or grade D equivalent to the German grade “ausreichend” (up to 4.0), you can still be admitted to a master's or MBA program. For this, you need:   

  • A bachelor's degree (grade 3.5 - 4.0) from a state or state-approved higher education institution/university 
    AND  
  • Relevant study achievements from a master's/MBA programme at a state or state-approved higher education institution/university relevant to the desired master's/MBA programme, with a minimum of 40 ECTS credits  
    OR  
  • A relevant completed master's/MBA degree from a state or state-approved higher education institution/university 
    OR  
  • Relevant qualifications outside of academia which can be credited to you such as further education/training at GQF7 level or – for foreign qualifications such as postgraduate diplomas – equivalent to GQF7 level relevant to the desired master's/MBA programme, with a minimum of 40 ECTS credits  

Tip: If you apply for recognition, we can review your relevant achievements and, where possible, credit them towards your study programme in a relevant field. 

Exception: To be admitted to the master's programme in Architecture (120 ECTS credits), you must have completed your undergraduate degree with a final grade of at least "good” or grade B equivalent to the German grade "good" (up to 2.5). 

Further admission opportunities

Is your undergraduate degree not in the required subject field for this programme's 120 ECTS points variation admission requirements? You can still apply! You'll have to take 2 specific courses at the start of your studies, and pass them successfully in order to continue with your studies. That way, you don't have to take an entrance examination, and can prove your skills while earning ECTS points as part of your studies.

Fee Reduction Programme

Apply for the Fee Reduction Programme and receive a discount on your tuition fees. 

Please get in touch with our Study Advisory Team for more details. 

English language skills

Depending on your personal circumstances, you might be required to provide proof of your English language proficiency. Your skills would need to match the B2 level of the Common European Framework (CEF). 

We accept the following English language skills certificates*: 

  • TOEFL (minimum 80 points)* or 
  • IELTS (minimum Level 6)* or 
  • Duolingo English Test (minimum 95 points)*
  • PTE Academics (minimum 59 points)* or
  • Cambridge Certificate (minimum Grade B)* 

Is English your native language, or have you graduated from an English-speaking school or university? Then you do not need to prove your English language proficiency. 

Get in touch with our study advisors for more details. 

*Proof must be provided before the start of the study and must not be older than five years. 

APS Certificate

If you are from India, China or Vietnam, you might need the APS certificate to study in Germany, regardless of if your programme is 100% online or on-campus. Learn more about the APS certification here.  

Careers

Your Machine Learning career outlook

Machine learning engineer working in his lab

Machine Learning Engineer

As a Machine Learning Engineer, you will focus on developing and deploying complex machine learning models. Your role involves collecting and analysing large datasets, creating algorithms that allow machines to learn from data, and optimising these models for performance. You'll tackle challenges in predictive modelling, computer vision, natural language processing, and more, significantly contributing to the advancement of AI technologies.

Professional in MLOps Engineering working with robots

MLOps Engineer

As an MLOps Engineer, you'll bridge the gap between data science and IT operations, ensuring seamless integration of machine learning models into production environments. You will streamline the lifecycle of ML models, from development and testing to deployment and monitoring. Your work will enhance model reliability and scalability, improving the efficiency of AI applications and enabling businesses to harness the full potential of machine learning.

A couple of product owners in machine learning working in a laboratory

Product Owner – Machine Learning

As a Product Owner for Machine Learning, you will lead the strategic development of AI-driven products and solutions. This role involves defining product vision, setting development priorities, and coordinating with cross-functional teams to deliver machine learning features that meet customer and business needs. You will ensure that ML components add significant value, driving innovation and maintaining a competitive edge in the market.

Student reviews

This is what our students say

  • “Thanks to my online studies degree in IT Management I could probably pass in any IT profession, because the content was very diverse.”

    Andreas Aumeier

    M.Sc. IT Management, Germany

  • “In general, IU is a very well equipped university with a perfect staff.”

    Mantas Paskevicius

    BSc Computer Science, Lithuania

  • “I am grateful for the high degree of flexibility when studying at IU, especially when it comes to online exams: I can take my exam in the middle of the night if I feel ready.”

    Sonja Svirac

    Online student

Read our success stories
Personal counselling
Have any questions?

Visit our FAQ page or get in touch with our Study Advisors.


Tuition fees

Online Study models & fees for your Master degree in Machine Learning

On campus study model and fees for your Master degree in Machine Learning

Depending on your personal or professional circumstances, you may wish to complete your studies as quickly as possible, or you may prefer a more flexible study programme that is less time-consuming. That’s why we offer part-time options for all our study programmes. This allows you to study alongside professional or personal commitments. We adjust your study fees based on your chosen time model.

Are you unable to finish your programme within the given time? No problem! If you realise that you need more time, you can simply switch to another time model with one months’ notice before the end of the month.

No registration or administration fees are charged when you apply for studying – you’ll only be charged once your studies have started, and the trial month has ended.

Your trial month begins when you receive your login credentials. This will give you the opportunity to test our courses for one month without obligation, before being charged. During that month, you can then take your first courses and start learning right away!

Once the trial month is over, your studies continue. You’ll pay your tuition fees according to your contract.

At IU, we believe in full transparency – so there are no hidden fees. You only pay for your tuition and the one-time campus registration fee of €1,500.

No registration or administration fees are charged when you apply for studying – you'll only be charged once your studies have started. If you won't be admitted to a programme because you do not meet the admission requirements, no fees will be charged.

Full-Time

Duration 24 Months

US$ 588
US$ 524 /mth* Apply now
* € 496 based on the exchange rate from 30.11.2024 12:00 AM (CET)

Part-Time I

Duration 36 Months

US$ 441
US$ 399 /mth* Apply now
* € 377 based on the exchange rate from 30.11.2024 12:00 AM (CET)

Part-Time II

Duration 48 Months

US$ 348
US$ 316 /mth* Apply now
* € 299 based on the exchange rate from 30.11.2024 12:00 AM (CET)

All our study programmes include the following benefits

  • Teaching and study material
  • Marking of your end-of-module exams
  • Monthly live and recorded tutorials
  • Use of the online campus
  • Individual study coaching
  • Online exams
  • Career coaching
  • Learn German and English for free
  • 4-week money back guarantee
  • Teaching and study material
  • Marking of your end-of-module exams
  • Individual study coaching
  • Online exams
  • Career coaching
  • Learn German and English for free
  • On-campus tutorials, 2-3x week
  • Access to all on-campus services
Recognition

Recognition of previous achievements

  • Save time: Skip individual modules or whole semesters!

Even before you apply for a study programme, we’ll gladly check whether we can take your previous achievements into account: 100% online, no strings attached. Simply fill in our recognition application form, which you can find under the content section of each study programme's webpage, and upload it via our upload section. You can also e-mail it to us, or send it via post.

Send an email to study@iu.org to find out which previous achievements you can get recognised. You can get your previous achievements recognised during your studies.

Do you need help with your application for recognition? Our student advisors will be happy to help. Simply arrange a personal call-back appointment.Arrange a personal video consultation appointment to discuss recognition

Recognition files

Guide to recognition

Individual application for recognition

Why IU International University of Applied Sciences is the best choice

Your Studies Are Flexible and 100% Online

Schedule when you want to learn and study 100% online. At IU you have the possibility to complete your degree fully from home, whether full-time or part-time. You can even take your exams online whenever it suits you. 

Accredited & Globally Recognised

IU is accredited and certified with a seal of approval from the German Accreditation Council. All IU study programmes, materials, and services meet high internal and external quality standards, which are regularly reviewed and updated. We can also provide you with an official Europass Diploma Supplement once you graduate, to ensure that your degree is recognised anywhere in the EU.

You Gain Full Support

We provide you with innovative learning tools, digital study material, tutorial videos, live teaching sessions, student advice and support. You also have 24/7 access to our large online library. Your tutors are always available to answer your questions. Our study coaches are also available to help at any time. 

The Ideal Mix of Theory & Practice

Our programmes provide you with essential theoretical knowledge and focus, above all, on practice-oriented studies designed to best prepare you for your future career. Thanks to our great variety of electives you can specialise in the specific areas that match your personal goals.

Accredited & Globally Recognised

IU is accredited and certified with a seal of approval from the German Accreditation Council. All IU study programmes, materials, and services meet high internal and external quality standards, which are regularly reviewed and updated. We can also provide you with an official Europass Diploma Supplement once you graduate, to ensure that your degree is recognised anywhere in the EU.

The Ideal Mix of Theory & Practice

Our programmes provide you with essential theoretical knowledge and focus, above all, on practice-oriented studies designed to best prepare you for your future career. Thanks to our great variety of electives you can specialise in the specific areas that match your personal goals.

Hybrid Studies = More Flexibility

By combining in-person tutorials 2-3 times per week with 24/7 access to online study materials, you get to benefit from a more flexible study schedule. This allows you to work alongside your studies, or combine other activities, with relative ease. 

You Gain Full Support

We provide you with innovative learning tools, intimate campuses, easy access to lecturers, live teaching sessions, student advice services, and career support. You also have 24/7 access to our large online library. Your tutors are always available to answer your questions – and so are our study coaches.  

FAQs

Is a masters in machine learning worth it?

Yes, a masters in Machine Learning is highly valuable, particularly in our data-driven era. It opens numerous career opportunities in technology, healthcare, finance, and beyond. Our online MSc Machine Learning at IU not only equips you with cutting-edge skills but also offers the flexibility to study from anywhere, making it a worthwhile investment.

What can I do after a masters in machine learning?

With a masters in Machine Learning, you can pursue roles such as Machine Learning Engineer, Data Scientist, and AI Specialist. Our IU online MSc Machine Learning graduates have successfully secured positions in leading tech companies around the world, utilising their advanced skills and knowledge to drive innovation.  

Who is eligible for Masters in machine learning?

Typically, applicants should have a solid background in computer science, mathematics, or a related field.

How long is a Masters degree in machine learning?

The duration of an online masters in Machine Learning can vary depending on your study pace. Full-time students can generally complete the programme in 2 years, while part-time students may take up to 4 years. At IU, our flexible online MSc Machine Learning allows you to tailor your studies to fit your schedule, ensuring you can achieve your degree without compromising your other commitments.  

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