Prepare for the hottest job in the tech age by mastering the skills in data science!
The Master of Computer Science in Data Science program consists of 60 ECTS credits coursework with a final project.
You can complete all modules in 12 months and earn your master’s degree in Data Science.
You are offered both digital and face-to-face learning experience throughout the programme.
Comprehensive digital course materials, projects and e-libraries are provided through our online platform while you can be part of a thriving on-campus experience involving workshops, hackathons, action learning groups and mentoring.
ELU has been awarded university status by YODAK in Cyprus and is pending accreditation by NVAO in Netherlands.
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.
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.
1- Motivation letter
2- Diploma or a document as proof of graduation (STEM related degree preferred)
3- English proficiency documents (If you didn’t have an English-medium instruction in your bachelor’s programme, IELTS: 6.5 or above, TOEFL: 90 or above required)
Our academic board will review your application and may call 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 tuition fee and start your programme.
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.
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.
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.
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.
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.
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.