About the program
What is data science and what can you do with it? This 7-day course (a total of 7 weeks) is targeted at professionals who want to learn to develop machine-learning solutions, and who are also interested to learn the business implications of data science.
- Introductory program in data science for professionals, based on the dual perspectives of Eindhoven University of Technology and Tilburg University.
- Participants can continue in the Data Science for Experts program: Level 1 (7 months-part-time) or Level 2 (1 year – part-time).
What you'll learn
An orientation
An orientation in data science, Big Data, new analytics and new business opportunities.
Predictive analytics
Predictive analytics, the theory of supervised and unsupervised learning, and their practical applications in a Python‐based analytics environment.
Apply
Applying machine learning in the data‐analytic workflow embodied by the CRISP‐ DM model.
Any questions? Or ready to sign up?
Contact our education advisory team
Practical information
- Completed Bachelor’s and/or Master’s degree and several years of work experience
- Affinity with analytics and IT, and the ambition to learn programming skills. Typical STEM background (science, technology, engineering, mathematics).
- Ambition to grow in senior professional position, combining technical expertise with boundary-crossing skills in leadership, entrepreneurship, complex problem solving and critical thinking.
- Preparation: Depending on your skill level in programming, you may need up to 4 weeks of self-study in an online learning environment where you will learn coding in Python.
- Introduction: Data science — new forms of data, new analytics and new opportunities. We discuss Big Data, predictive algorithms, machine learning and AI. We discuss typical applications, ranging from data science to make current processes and services more efficient, to new products with smart features, and data and analytics as a basis for new business models.
- How does data science work? We discuss data-analytic thinking and the CRISP-DM model for data-science projects. We develop a fundamental grasp of the main steps of a data-science project: translating a business goal to a data-science question, finding and accessing data sources, extracting features from data, training and selecting a machine-learning algorithm, evaluating the performance and deploying the algorithm in a machine-learning pipeline.
- We develop and discuss practical implementations of machine learning and data engineering in a Python-based analytics environment.
We believe in Data Scientists being T-shaped professionals
The T shape visualizes the idea that a successful career is based on the combination of deep technical expertise (the vertical bar) and wide and broad boundary-crossing skills (the horizontal bar).
Data scientists master the technical skills of data engineering, and know how to use data-warehouses, build a data pipeline and access Big Data cloud solutions. They have the analytical skills of machine learning, and can translate a business opportunity into a data-science problem, apply the data-analytic workflow to develop a model, and test and implement it in a Python environment.
Data scientists are also business savvy, understand how business models and strategies work, are able to manage data-science projects delivering results, and in general, know what it takes to get things done in large and complex organizations.
Talk to our teachers and discover your optimal development path.
Relevant courses
Level 1
Level 1 - Data Science for Experts
Level 2
Level 2 - Data science for Experts
Brochure Download – Data Science & AI for Professionals
And discover the possibilities of our Foundation program.