Data Science for Health Professionals

Duration 7 months (Level 1)
1 year (Level 2)
Weekly workload 8 hrs (class) + 8 hrs (preparation and assignments)
Start date November 10th, 2023
Tuition fee €9,950* (Level 1)
€18,950* (Level 2)

Data Science for Health Professionals

In Healthcare every decision matters. Do you believe there is a lot more potential in data than we are using right now? Do you have the ambition to be a pioneer in unlocking data and information to support decision making processes? This program is targeted at medical professionals and managers in healthcare eager to learn how to integrate data and analytics into their work.

  • Certificate program in data science for professionals in Health, based on the dual perspectives of Eindhoven University of Technology and Tilburg University.
  • Program can be completed at level 1 (7 months) or level 2 (1 year).
  • Introduction into the JADS Data-Science Community: a network for life-long learning for data-science professionals.

*= Ask for our social rate for Healthcare and/or Public professionals

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You walk away with

  1. Solid and hands-on understanding of machine learning and data engineering.
  2. Practical data entrepreneurship, knowing the value that Big Data and analytics could bring to healthcare, and mastering the skills to translate goals and challenges to data-science questions.
  3. Capability to define a good data-science project and organize a data-science team, and an understanding of the managerial challenges of shaping the analytics ambitions of the organization.
  4. Understanding of the opportunities and practical applications of data science in healthcare.
  5. A completed data-science project in your own organization; data science learnings not only applicable to the participant but to the whole data team.
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Do you fit the profile?

  • Completed Bachelor’s and/or Master’s degree and several years of work experience.
  • Health professionals and managers eager to learn how to integrate data and analytics into their work.
  • Bridge between analytics teams and healthcare professionals and management.
  • Ambition to grow in senior professional position, combining technical expertise with boundary-crossing skills in leadership, entrepreneurship, complex problem solving and critical thinking.
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  • Certified Data Scientist in Health (Level 1, 7-month program).
  • Certified Lead Data Scientist in Health (Level 2, 1-year program).
  • Certificates issued by JADS on the basis of the quality of the group assignment (Level 1) or individual assignment (Level 2)

What you will do

  • Foundation:
    • Orientation in data science: Big Data, new analytics and new opportunities in health.
    • Machine learning: theory of supervised and unsupervised learning, predictive analytics, and exploration of the analytics landscape.
    • Data-analytic workflow as embodied in the CRISP-DM model.
  • Level 1:
    • Core program in data analytics, data engineering and data entrepreneurship.
    • Healthcare-specific program: opportunities and typical applications of data science in health, such as computational personalization, ethics, and playful intelligence.
    • Complex and challenging group project, where you and your team develop a realistic data-science solution based on the NHS PROMS dataset.
  • Level 2:
    • Advanced-level program, including privacy law & data security, data leadership & entrepreneurship, process mining, anomaly detection, practical deep learning and other advanced applications.
    • Electives, including advanced data architectures, data science and cognitive science, advanced machine learning & AI, and business analytics.
    • Boot camp: This two-day experience revolves around different teams and one data challenge to be solved, following the format of a hackathon.
    • Professional skills: Lectures and individual coaching in taking a leading role in the development of your organization’s data ambitions.
    • A data project within your own organization supported by JADS experts.
Detailed curriculum

Teaching & Learning methods

Teaching does not start from theory and technology, but from challenging assignments. Real challenges make learning motivating, helps to get your organization involved, and is a catalyst to achieving real impact. During the program, you complete three CRISP-DM data-science projects:

  • A stylized team assignment in the Foundation program.
  • A complex and realistic group assignment, supported by technical experts and the Communities’ Academic Directors in the Level 1 program.
  • A substantial project in your own organization, supervised and supported by JADS experts (Level 2 program). Emphasis in the graduation project is less on technical implementation, and more on the development of opportunities for healthcare, innovation strategy and a deployment or transition plan.

Things you will like

  • The JADS Community: Upon entering the programs as from level 1, you will be part of the JADS Community of companies, students, startups, professionals, NGOs and academic staff, who all have a passion for data science. We organize network events, inspirational talks and many other activities. It’s also a market for finding business partners and expert help for a data challenge. The Community embodies our belief in the importance of life-long learning.
  • The Mariënburg, a former convent in the historical center of Den Bosch, is JADS’ home. It’s a welcoming, inspirational and atmospheric environment for life-long learning, with the former chapel functioning as the main auditorium, and the vast complex offering many surprising authentic details reminiscent of its former function.
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What we believe in…

Data scientists are 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.

Data science is changing what organizations do

Data-science applications in professional organizations range from initiatives to make current processes and services more efficient common applications are in smart maintenance, production planning, marketing, product and reliability improvement, anomaly detection and early warning systems. But organizations should also think beyond the horizon of current products and services, as data science is creating important


Any questions? Get in touch with our Professional Education Team!

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