〉 The development of job-ready skills, as identified by data science experts
〉 The best digital content and an extensive e-library with interactive live workshops
〉 A personal mentor working in the field of data science
〉 Introductions to partner employers in the Amsterdam commercial area
Month 1 - 7 | Online
Month 8 - 11 | Online + Amsterdam
Month 12 - 16 | Talentship/Practicum - Global
Dubbed the hottest job of the 21st century, data scientists are some of the most wanted professionals in today’s labor market. According to Glassdoor, data science is the number one job considering demand, salary, and job satisfaction. In Amsterdam, the average entry-level data scientist salary is 47,422 EUR
ELU helps you prepare for the world’s hottest job by developing your technical and interpersonal skills and connecting you with employers in the Amsterdam metropolitan area.
Total duration of the Master Programme is 16 months. You should commit 12-20 hours per week to your learning.
upon gaining salary income
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.
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.
This quick form will help us understand whether you meet the basic requirements
If your profile is shortlisted, you are invited to an online analytical test and asked to submit a statement of motivation.
Upon enrolment we will ask for a copy of your undergraduate diploma and transcript, as well as proof of English proficiency.
– An undergraduate degree in Computer Science or a related field
– Knowledge of programming (Python preferred) and statistics
– Professional experience in the field of IT/tech incl. software development, engineering, consultancy,
If you are unsure whether you meet the prerequisites for the course, please write us at email@example.com
SCIENCE PARK 408 1098 XH AMSTERDAM