Exchange courses in Applied Computer Science
Spring 2027
A programme for international exchange students who have obtained at least 60 ECTS in the study field of Applied Computer Science, on bachelor level.
*The course is officially taught in Dutch. Nevertheless, for incoming exchange students, English-language support will be provided.
For official course catalogue information check the course catalogue: Course Catalogue 2026-2027 (available from june 2026). Below you can find a description of the course contents.
.Net Essentials
This course introduces students to the foundational concepts and practical skills needed to develop Windows‑based desktop applications using C# and the .NET framework. Students learn to analyse problem statements independently, identify inputs and requirements, and translate them into correct algorithms and working code.
A strong emphasis is placed on object‑oriented design. Students convert problem descriptions into class‑based architectures and apply key principles such as inheritance, interfaces, and polymorphism to create flexible and maintainable software. They learn to use Visual Studio effectively, document their own classes according to Microsoft guidelines, and integrate built‑in .NET classes into their applications.
The course explores essential programming constructs—variables, methods, control structures, debugging, arrays, string operations, data structures, and file handling—while gradually introducing more advanced techniques. Students also practice improving and refactoring existing code and learn to debug step‑by‑step with the tools provided by the .NET environment.
By the end of the course, students can design, implement, document, and test simple yet robust desktop applications in C#, using solid object‑oriented techniques and good programming style.
Web Scripting
This course introduces students to the core programming concepts needed to build dynamic, interactive web applications using JavaScript. Students learn to apply object‑oriented principles in JavaScript, working with modules and Node.js to structure code cleanly and effectively.
A central focus lies on creating dynamic web pages through DOM manipulation and event handling, enabling students to respond to user actions and update webpage content in real time. They also learn to interact with external data sources by calling REST APIs and integrating JSON into their applications.
The course further explores functional programming elements in JavaScript, giving students a broader understanding of modern JS development patterns.
By the end of the course, students can design and implement interactive web pages, work with APIs and structured data, and build Node.js applications that apply both functional and object‑oriented programming techniques.
This course provides a foundational introduction to Artificial Intelligence and Machine Learning, giving students the essential tools to understand, analyse, and work with data in a systematic way. Students learn to explain key AI and ML concepts, distinguish between different types of machine‑learning approaches, and apply fundamental algorithms to simple problems.
A core component of the course focuses on probability and basic statistics, enabling students to describe uncertainty and draw insights from data. They learn to clean and analyse datasets, handle missing values and outliers, summarise information effectively, and evaluate the quality of existing data representations.
Using Python and Jupyter Notebooks, students gain hands‑on experience with data processing, visualisation, and exploratory analysis. They learn to extract relevant information from problem descriptions and design suitable solution strategies based on the available data.
By the end of the course, students can interpret datasets critically, apply basic ML techniques, and translate problem statements into workable analytical approaches—laying the groundwork for more advanced AI and machine‑learning studies.
System Essentials Windows
This course introduces students to the fundamental concepts behind operating systems, computer hardware, and modern IT infrastructures. Students explore the historical and theoretical foundations of operating systems, learn how they manage processes, memory, users, and permissions, and gain hands‑on experience working with both graphical interfaces and command‑line environments.
A strong practical component guides students through installing, configuring, and maintaining operating systems—both on physical hardware and in virtualised environments. Students learn to use terminal commands, manage users and groups, work with files and directories, and perform system administration tasks. They also develop scripting skills to automate maintenance and configuration.
The course provides an introduction to server systems, essential services, and PowerShell, with a particular focus on Microsoft technologies. Students explore on‑premise infrastructure alongside modern cloud concepts, gaining experience with both environments and understanding how they complement each other.
By the end of the course, students can set up and manage a functioning server environment, understand core hardware components, work confidently with system
tools, and apply best practices for maintaining secure and reliable operating systems—preparing them for more advanced infrastructure and sysadmin roles.
Security Essentials
This course introduces students to the core principles of cybersecurity, providing both the theoretical background and the hands‑on skills needed to understand and defend modern digital environments. Students learn to distinguish the characteristics and motivations of both cybersecurity professionals and cybercriminals.
A central part of the course focuses on the CIA triad—confidentiality, integrity, and availability—and how these principles guide secure system design and defense strategies. Students study and practice common attacker techniques, tactics, and procedures (TTPs) as well as the corresponding defensive measures, gaining insight into how real‑world threats emerge and how they can be mitigated.
The curriculum covers essential topics such as malware, common cyberattacks, security legislation, and industry‑standard frameworks like the OWASP Top 10. Through guided exercises, students learn to recognise, explain, and apply various attacks within a controlled environment, and to test their own applications for vulnerabilities and weaknesses.
Each chapter combines theory with practical assignments, and learning is supported by additional seminars, labs, exercises, and videos. By the end of the course, students can analyse threats, apply defensive techniques, and approach cybersecurity challenges with a structured, professional mindset.
X-perience
This course supports students in their personal and professional development by encouraging initiative, curiosity, and engagement within a rapidly evolving IT landscape. Students actively explore new knowledge, skills, and attitudes beyond the standard curriculum, broadening their understanding of IT in both business and international contexts.
The used approach fosters innovation, entrepreneurial thinking, and multidisciplinary collaboration. Students follow trends in the IT sector with empathy and openness, respond to new opportunities, and expand both their personal network and the network of the programme. They reflect critically on their growth, strengthen existing competencies, and develop new ones through continuous self‑assessment.
The course spans several domains—internationalisation, seminars, innovation, personal development, and student engagement—and students gather evidence of their
progress in a structured e‑portfolio. This portfolio documents achievements, insights, and reflections, helping students articulate their development as emerging professionals.
By the end of the course, students demonstrate a mature and professional attitude, and take ownership of their learning journey within a dynamic and globally oriented IT environment.
Machine Learning
You’ll learn the basic principles in the domain of Machine Learning. As data is the main resource in this domain, you will learn to gather, understand and process data from different sources. Data visualization is an important topic and is covered as well in this course. Some necessary mathematical components are covered to be able to understand the workings of all covered mechanics in Machine Learning.
In a group project, you’ll use the gathered knowledge to create a working data solution.
- Essential concepts in Machine Learning
- Data collection and data analysis
- Data visualization
- Data quality & data cleaning
- Structured & unstructured data
- Supervised learning
- Unsupervised learning
- Evaluation of AI solutions
AI Algorithms and Computer Vision
During this course, common solutions for classical AI problems will be tackled. The course serves as an introduction to classical artificial intelligence and computer vision. You will learn about fundamental data structures, time- and space-complexity and essential algorithms. In the domain of computer vision, all basic operations will be covered, so you’ll be able to preprocess image data for further use in all kinds of AI applications.
In a group project, you’ll use the gathered knowledge to create a working AI solution.
- Multiple concepts within classical AI
- Solve AI problems with algorithmic solutions
- Relevant data structures and search algorithms
- Compare solutions using time- and space-complexity
- Analyze and process image data with basic computer vision techniques
Web for AI
In this course, you’ll learn to create (responsive) web applications, using popular frontend frameworks (React, Vue, Angular, Bootstrap, …) You will be able to create a prototype to test or showcase an AI-application using web technologies.
Furthermore, you will learn to communicate with external REST APIs to enrich web applications with AI services. Finally, you will be able to enable your own AI solutions through a custom-made REST API in Python, so they can be used in other web applications.
- Responsive web applications with CSS frameworks (Bootstrap)
- Web applications with JavaScript framework(s)
- Communicate with external REST APIs
- Explore existing AI web services and learn to integrate them in custom web applications
- Create RESTful web services with Python framework(s)
- Integrate own (AI) solutions in a custom REST API
- Combine all of the above to create a functional web application
X-perience
This course fosters students’ personal and professional growth in a rapidly evolving IT landscape. Students cultivate an entrepreneurial mindset, seize initiatives, and proactively engage with emerging technologies and application domains. They expand their knowledge, skills, and attitudes beyond the core curriculum, gaining a broader perspective on IT in business and international contexts.
Through activities in internationalization, innovation, personal development, and student engagement, students hone their professional attitude and communication skills. They adopt a systematic, project-based approach, demonstrating curiosity, empathy, and hands-on learning.
A central element is building an e-portfolio, where students compile evidence of their progress, critically reflect on their learning journey, and outline a clear personal development plan. This process helps them recognize their evolution as emerging IT professionals and pinpoint areas for growth.
By course end, students can confidently position themselves in a dynamic sector, communicate effectively with internal and external stakeholders, and contribute meaningfully to the wider IT community.
Security Advanced
This course provides an in‑depth, practice‑oriented exploration of advanced cybersecurity domains within an enterprise context. Students learn to classify organizational security needs using the infosec color wheel and to relate different security roles and activities to concrete business risks.
Core topics include Open‑Source Intelligence (OSINT), reverse engineering, malware analysis and deception, web application vulnerabilities (such as cross‑site scripting and injection attacks, aligned with the OWASP guidelines), digital forensics, incident response, penetration testing, mobile and API security (including OAuth 2.0), and secure coding practices.
Throughout the course, students work in realistic lab environments where they identify, exploit, and mitigate vulnerabilities in a controlled and ethical manner, applying both offensive and defensive techniques. They independently research potential attack vectors, implement technical countermeasures, and document their findings in professional reports. Team‑based assignments strengthen their ability to collaborate across security functions, communicate risks clearly to different stakeholders, and reflect on the role of each color in the infosec color wheel.
By the end of the course, students have a solid technical foundation in multiple cybersecurity disciplines and the practical skills needed to operate effectively in an enterprise security team.
Research Project AIN
You are part of a group of several students. It is your task to deliver a working AI application based on a problem description. These assignments are created in such a way that they correspond to what the students are taught in the course 'AI Algorithms and Computer Vision', 'Web for AI' and 'Machine Learning'.This knowledge is applied in a concrete project with an emphasis on Rapid Prototyping.
The project team uses agile methodology to streamline the process throughout several sprints. The project runs throughout the semester and is divided into a number of work packages, including analysis, design, planning, research, implementation, documentation and presentation.
In the project week and this course, the following topics regarding professional and personal development are discussed through different workshops: how to communicate - feedback rules, group dynamics, time / self-management and conflict management within teams.