Bachelor in Data Science and Knowledge Engineering
Maastricht, Netherlands
DURATION
3 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
EUR 2,060 / per year *
STUDY FORMAT
On-Campus
* The statutory fee for this programme is: €2,060. The institutional fee for this programme is: €10,000
Scholarships
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Introduction
Why this programme?
Knowledge is central to modern society. Smart chips help companies keep track of goods and manage supplies and stocks. New, high-tech communication devices, such as mobile phones, navigation instruments, and digital cameras, are greatly enhanced by intelligent software and medical and biological engineering help medical doctors arrive quickly at accurate diagnoses.
As a Data Science and Knowledge Engineering student, you'll study methods to approach new challenges in these important areas. You’ll generate new knowledge by gathering and ordering valuable information using mathematics and intelligent computer techniques. The knowledge you'll acquire can, in turn, be used to make decisions or solve problems efficiently.
Admissions
Curriculum
Building bridges between theory and practice
In contrast to more traditional programmes in computer science and mathematics, Knowledge Engineering takes a targeted, practical and applied approach. You'll learn to build bridges between theory and practice and you’ll be able to apply solutions to data problems in a broad range of settings, such as logistics, robotics, and medicine. You’ll use techniques from:
- computer science, with an emphasis on software, programming, algorithms, and logic
- applied mathematics, including the practical application of major mathematical concepts, methods, and techniques
- artificial intelligence, including ways to reason using available knowledge and an introduction to machine learning and intelligent search
Project-Centered Learning
Project-Centered Learning (PCL) is an innovative, application-centered instructional method used at DKE. You'll work on projects in small groups of 5-6 students, applying recently acquired knowledge to open-ended problems, that are often based on real-world situations. The assignments you'll work on are may be provided by companies and organizations in healthcare, IT and logistics. You could, for example, be asked to develop a program that records river water levels and issues timely flood warnings for a local government. But you may also be asked to study the traffic flow at major highways and road junctions and come up with effective ways to manage them.
A study in an international environment
The job market for knowledge engineers is an international one, so chances are that you end up working overseas, or at an international company. This means you must be able to work with people from many different cultural backgrounds. Few places could be better situated for this than Maastricht. Students and staff come from all over Europe and the rest of the world, and Maastricht itself is at an international crossroads between the Netherlands, Belgium, and Germany. Two-thirds of our students come from outside the Netherlands, and such diversity creates a strong international atmosphere.
Spend the first semester of your third year abroad
As a Data Science and Knowledge Engineering student, you’ll have the opportunity to spend the first semester of your third year abroad. Studying abroad is not mandatory in this programme. DKE has exchange partners in Australia, Denmark, Canada, China, Hong Kong, Iceland, Italy, Singapore, the United States and Switzerland.MaRBLe honors programme
Through the Maastricht Research-Based Learning programme, MaRBLe for short, we offer talented third-year bachelor’s students the opportunity to conduct their own research project. You will be guided by experienced academic staff who will help you further develop your critical thinking and research skills. This will help prepare you for a career in scientific research or research positions in business.
Curriculum
First Year
- Introduction to Data Science and Knowledge Engineering KEN1110
- Introduction to Computer Science 1 KEN1120
- Discrete Mathematics KEN1130
- Computational and Cognitive Neuroscience KEN1210
- Introduction to Computer Science 2 KEN1220
- Linear Algebra KEN1410
- Project 1-1 KEN1300
- Calculus KEN1440
- Data Structures and Algorithms KEN1420
- ICT and Knowledge Management KEN1430
- Numerical Mathematics KEN1540
- Software Engineering KEN1520
- Logic KEN1530
- Project 1-2 KEN1600
Second Year
- Databases KEN2110
- Philosophy & Artificial Intelligence KEN2120
- Probability and Statistics KEN2130
- Reasoning Techniques KEN2230
- Machine Learning KEN2240
- Graph Theory KEN2220
- Project 2-1 KEN2300
- DKE Honours Programme - MaRBLe 2.0 (2-1) KEN2320
- Mathematical Modelling KEN2430
- Human-Computer Interaction and Affective Computing KEN2410
- Theoretical Computer Science KEN2420
- Linear Programming KEN2520
- Mathematical Simulation KEN2530
- Social Media KEN2540
- Computer Security KEN2560
- DKE Honours Programme - MaRBLe 2.0 (2-2) KEN2620
- Project 2-2 KEN2600
- Text Retrieval Systems KEN2550
Third Year
- Project 3-1 KEN3300
- Data Analysis KEN3450
- Operations Research Case Studies KEN3410
- Intelligent Systems KEN3430
- Bachelor's Thesis KEN3500
- DKE Honours Programme - KE@Work (3-1) KEN3310
- DKE Honours Programme - MaRBLe 2.0 (3-1) KEN3320
- Study Abroad KEN3600
Electives
- Semantic Web KEN3140
- Game Theory KEN3130
- Prolog KEN3234
- Robotics and Embedded Systems KEN3236
- Software and Systems Verification KEN3150
- Logic for Artificial Intelligence KEN3231
- Parallel Programming KEN3235
- Introduction to Bio-Informatics KEN3440
- Secure Web Applications KEN3237
- Study Abroad KEN3600