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Data is a key asset in our economy and social environment. On a daily basis we see new initiatives to make more use of data. In this joined minor Data Science of HAS University of Applied Sciences and Avans you will be working in a multidisciplinary team to explore today’s complex data-related opportunities. You will be working on real business cases provided by various organizations. The projects will focus on the agrifood business domain.

About the program

The focus of the minor is to discover, and gain experience in the application of data science in a real project situation.

The first 2 weeks focus on a global introduction on data science and in agrifood and to get to know the tutors and your fellow students.

The next period focuses on data science classes and agrifood domain classes. These should give you the entry-level to start the projects. You will practice your new skills in various small assignments.

In week 6 you will select the project you will be working on for the remainder of the minor. Together with your fellow students, you form a multi-disciplinary team to work on the project.

This minor is a cooperation between Avans and HAS University of Applied Sciences

learning goals

  • The student can value current precision sensor systems and data science techniques and their application (datascience) in the field of agrofood and come up with arguments and ideas for alternatives, so that he can be a true equal in consultations and discussions in the field of smart farming
  • The student is able to form a vision on how smart farming can be used to create an international/social sustainable system in the future
  • The student can reflect on one’s personal performance and progress in knowledge and skills in datascience and the field of smart farming, so that he can constantly develop himself
  • The student can use existing algorithms and understands the underlying statistics in such a way that he can adequately solve a problem
  • The student can recognize the data components of a business problem and offer a solution using data science techniques.
  • The student can talk to the client and analyze the client’s real problem in a discussion with the client to touch upon the underlying questions and problems.
  • The student can collaborate with peers from similar and different disciplines in such a  way that he can integrate ideas logically in an advice
  • The student can recognize the smart farming components of a business problem and offer a solution using smart farming techniques.
  • The student can integrate knowledge and methods from other areas of expertise into his/her own (multidisciplinarity) in order to combine insights to solve problems
  • The student can explain the decisions and data science steps that lead to the advice to have a logical and substantiated advice.
  • The student uses communication theories and models and commercial skills to advise the client and reflect on the advisory process.

Application

Want to sign up for Data Science?

Here you find more information about the application procedure.