Master of

Data Science

Prepare for the hottest job in the tech age by mastering the skills in data science!

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Remaining Seats



15 - 16 Months

Education Method
Campus + Online
€9.000 in total
Estimated Salary
€54K -

Programme Overview

The Master of Data Science programme consists of 60 ECTS credits coursework with a final project. 
You can complete the first 7 months fully online, then you are expected to come to Amsterdam. Here, you meet our partner employers and start your job while you continue your master programme at ELU. We assist you in the process of landing your job, obtaining your visa and relocating. Comprehensive digital course materials, projects and e-libraries are provided through our online platform while you can be part of a thriving educational experience involving workshops, hackathons, action learning groups and mentoring.

Equip Yourself with the Right Skills


Use Python to manipulate, analyze and visualize data


Import data from various different sources


Convert raw data into a form ready for analysis. Tidy and clean data for analysis. Implement data manipulation techniques prior to analysis.


Explore large sets of data. Communicate and present visually critical data-driven findings and insights.


Apply statistical method to infer meaning from data and test hypotheses. Find the relationships in the data.


Build predictive models based on structured and unstructured data. Determine the right approach to solve problems. Compare models for accuracy and efficiency to find an optimal solution.

... and our unique educational model will get you there

Our educational model enables you to earn your data science degree while you practice skills through workshops and meetups, action learning groups and work-based projects. Our mentors and facilitators support and guide you in your learning journey.
You not only gain mastery in the science of data but also learn the art of leadership to become a change agency in your organisation.

Application Process



Fill out the application form. It only takes a few minutes.



If your profile is shortlisted by the Academic Board, we will ask you for a Statement of Purpose and invite you to an analytical thinking test. You might also be called for an interview for a final decision.
You will then be notified about the result of your application and scholarship offer.



Upon selection, you can complete your application process by paying the registration and the tuition fee, and finally start your programme. You may also be asked to submit supporting documents (diploma or a document as proof of graduation, transcript, and English proficiency documents).


Engage with each other and the programme, and explore the data science domain and essential data science competencies in this module. Discover your learning preferences and practice how to work with your action learning group. Acquaint yourself with the learning tools & resources and learn how to build your professional e-portfolio to showcase your skills in data science for prospective employers.


Master the basics of data analysis with Python – the most powerful programming language used by data scientists. This module gives you a practical start with data visualisation and Python essentials such as functions, iterators and lists.

90 HOURS / 3.5 ECTS

Learn how to get the data you need for your data science project from different sources like Excel files or the Web through APIs, and prepare your data for better analysis. Get serious by exploring your data more deeply and discover new insights.

115 HOURS / 4.5 ECTS

Advance your skills in data analysis and data manipulation in pandas – the most widely used Python library for data science and learn how to interact with relational databases and build your own in this module.


Join the 2-day data science hackathon in Amsterdam, build a project with your team and get the chance to network.

No Credit

Become a master at communicating your insights by creating interactive data visualisations and hone your hacker statistics toolbox by performing statistical inferences, constructing and testing your hypotheses.

130 HOURS / 5 ECTS

Learn how to utilize advanced techniques in data science to not only build & tune predictive and deep learning models but also make sense of networks by using real world network data.

116 hours / 4.5 ECTS

Develop your leadership skills in data science focusing on three key areas in leadership: Self-Leadership, Agile Fundamentals, Agile Leadership and Leadership 3.0.
This module also aims to provide you with sufficient knowledge of a range of methods within an action research framework to enable you to design and plan a work-based final project focused on advancing individual professional practice and making a contribution to your organisation.

390 hours / 15 ECTS


Nidhi Kumra

Data Scientist / ELU Course Facilitator

Branko Kovac

Data Scientist / ELU Course Mentor

Ioannis K. Breier

Data Scientist / ELU Course Mentor