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Data Engineering

Exchange programme

Do you ever wonder how companies get all this information about you? And how reliable this information is and what can be done with data? Are you not afraid to dive deep in to the data matter with several experts? Then the Data Engineering programme is for you.

In this programme you will research which data models can be used and how to use them. You will explore the ethical, technical and business issues of data. You will discover how to creatively and robustly apply Data Engineering while purpose and target groups of your products will be key.

This is achieved by involving several companies and organisations that give you the opportunity to work on real data engineering challenges in a small group and in a relevant and real context. Further, you will attend several guest lectures and meet-ups with (inter)national data engineering experts who will share their knowledge of the data engineering domain.

Facts and figures

The programme at a glance

Programme information

What to expect

About the programme

Programming

Students must be aware that programming is an essential element throughout this programme. Please prepare yourself before the programme starts if you have very little programming experience (for example in Python) 

Examples of projects in the programme

  • Combine weather data with pricing data and create a data value chain that can set pricing based on a pricing algorithm the customer already has and the long term weather predictions for a region.
  • Create an interactive knowledge platform for the full scale data architects and integrate already available knowledge in it.
  • Use data collected in trains to create a service to customers that will help them find the doors to the best available seat on their train based on their current location and time and analyse the usage of this service.
  • Use data collected in trains to predict service necessities to prevent delays due to technical errors.
  • Help a primary school group to utilise their data more efficiently.
  • Talks with other possible companies and organisations are still in progress.

 

Method

This programme does not have separate modules of different ECTS that have a combined total of 30 ECTS. The 30 ECTS are awarded in full at the end of the programme. In order for the students to obtain the learning goals and to monitor progress the students are required to have an active role in the following four factors:

  • Portfolio
  • Individual Research report
  • Group project
  • Feedback processing

Each part is 25% of the grade. All parts must be passed to obtain the 30 ECTS of the programme. During the programme peers, lecturers, experts will assess your work and provide feedback. In several iterations you will use this feedback to improve your knowledge and deliverables.

Working methods

Next to extensive participation of organisations, theories will be presented about the workings of data transformation techniques and you have the opportunity to use the latest technologies next to working on your research skills. Every week an expert in the field will provide a workshop because the world of digital development and users doesn’t stop. We zoom in on issues that will connect with your previous knowledge and interests and will fit with the project your group chooses. With current cases we will provide a motivating enrichment of your study and possibly the start of a promising career in the data field.

Learning materials

For this module no specific materials need to be acquired, you do need to bring your own laptop. The materials provided will consist of (recent) publications, materials provided by the guest lecturers, links to relevant videos and examples of data engineering applications

 

Learning outcomes

If you have successfully completed this exchange programme then you are able to:

  • Realise a data value chain for a real life organisation. This data value chain will provide a means to re-use data (collected for other goals) in a meaning full way for the organisation. 

By the end of this course you will learn the following:

  • You can research current issues of the target organisation in the data engineering domain;
  • You have acquired knowledge and insight with regard to one or more topics in the data engineering domain that fit into the subjects in the overall lesson plan;
  • You show the groundbreaking ability to make the transfer from technical knowledge acquired earlier in the course to a new application domain and as a member of a group with fellow students to devise, design and realize an innovative;
  • Data collection solution;
  • (information) Facts solution;
  • Information derivation solution;
  • Information delivery solution;
  • You have immersed yourself individually in a data problem, by investigating and analysing the problem, you have chosen an aspect based on your own judgement on the current situation of the problem and the degree of priority and attention given to this by the company;
  • Convincingly present your own innovative solution for the data problem investigated, e.g. in an elevator pitch, so that the audience of experts does not only gain insight into the content technology and the important aspects of the solution, but are also willing to further develop this solution in a follow-up project;
  • You can apply professional feedback in your implementation and justify this in your portfolio.

Calendar

Period 1     
Week 1 Introduction to the programme, project groups and project assignments, introductory lectures
Week 2 - 8 Combination of (guest)lectures and working on the data engineering project (supervised and unsupervised)
Week 9 - 10 Half-way assessments of progress
Period 2 
Week 1 - 7 Combination of (guest)lectures and working on the data engineering project (supervised and unsupervised)
Week 8 or 9 Final assessment
Week 9 or 10 Optional resit opportunity

Awarding

After completing your exchange programme at Rotterdam University of Applied Sciences, you will receive a:

  • Transcript of records

Four factors

An indication of the essential factors

Location

Where you can find us
Foto van locatie Location

Wijnhaven 107

Wijnhaven 107 3011 WN

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