Data Science Industry Track

Learn how to execute a Data Science Project
Companies are gathering masses of data on a daily basis but struggle to get the most value out of it.  Are you ready to make the digital transition by intelligent use of Data Science and gain a competitive advantage by bridging the gaps between engineering, business and Data Science? Develop yourself by determining your own growth path and become a Certified Data Science professional in your field of work. In 20 Fridays you will learn how to execute a Data Science Project.
Contact
​Chantal Stevels
Program Coördinator
​c.v.stevels@jads.nl
+31 (0)40 247 4100
Join our information session on one of the following dates and get to know more about JADS and our Tracks! ​
  • 10th of December 16.00 - 16:45
  • 14th of January 19.30 - 20:15
  • 28th of January 16.00 - 16:45
  • 11th of February 19.30 - 20:15
  • 25th of February 16.00 - 16:45
  • 11th of March 19.30 - 20:15
  • 25th of March 16.00 - 16:45
  • 1st of April  19.30 - 20:15
Register now for online session
Executing a Data Science Project
In this track you will learn how to execute a Data Science project. You will experience how to apply technical knowledge to your own relevant business issues and work on your own Data Science Project.

Courses you will encounter in this track will be (a.o.): Predictive Maintenance, Text mining / Natural Language Processing, Forecasting & Supply Chain Management, New Business Concepts & Servitization and Smart Maintenance.
 
After completing this track, you will receive an official JADS certificate signed by Tilburg University and TU/e and have the possibility to join the JADS Community or move on to the Leading in Data Science Track.
Fast Facts Industry Track: 
​Duration: 18 - 20 weeks
Time: 20 Fridays
Weekly hours: 16
Location: 's-Hertogenbosch/ Online
Next start:  May 2021
Tuition fee: € 9,950 VAT exempt

After the Industry Track you have learned:

  • Why business and data understanding are essential when applying Data Science in your own organisational context
  • What data engineering and data preparation contains
  • How to Execute your own Data Science challenges from beginning to end, using the CRISP-DM method to solve your specific business issue​
  • To apply insights hands-on to solve Data Science challenges; a Data Science project forms the basis of these insights
  • How to understand data and create insights gathered from data solutions and all other available data sets
  • Which Professional skills you need to develop to successfully execute a Data Science Project
The team you will learn from
Get educated by the best of both worlds. Professionals and professors associated with two universities combining technological with business expertise, research and knowledge. People with experience and passion, who combine academic research and real-world business expertise. This is where science and business come together.

For more information about our lecturers, download the brochure

JADS Community

Sharing knowledge and learning does not stop after you get your certificate. You will become part of the JADS community. We believe in Lifelong Learning. We will help you to continue to discover what Data Science knowledge and skills are best for you to maintain and improve upon. Being part of this community means that you can strengthen your network, work with and learn from peers and professionals. The JADS community is a network of professionals, students and teachers from different fields who come together to share ideas and knowledge.

Any questions? 

Leave your data with us and we will get in touch! 
Join our information session here.
Or send an email to professionaleducation@jads.nl
Data Science Lead Track: 38 days (1 year)
€ 18,950
This track has been compiled to fit your personal and professional needs and combines Data Engineering, Data Analytics and Entrepreneurship to create Business Impact.

​After this Track you will have all the insights and professional skills you need to not only execute but also lead a Data Science Project within your own organisation.
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