Certificate Programs in Applied Health Informatics

Flexible further education – apply knowledge directly

Expand your expertise in Applied Health Informatics quickly, practically, and alongside your career, perfectly tailored to your career goals.

Would you like to expand your know-how in the field of Applied Health Informatics and broaden your expertise without starting a degree program? Our certificate courses are specially tailored to the needs of working professionals: practical, flexible, and clearly structured.

Whether individual modules or combination modules – you choose what suits your professional goals and schedule. All certificate courses are awarded ECTS credit points and can be fully credited toward a master’s degree upon successful completion. This allows you to benefit from maximum flexibility.

Combination modules – three modules in one package, a big plus for your career

Our combination modules consist of three thematically coordinated master modules that take place in the same semester. This allows you to acquire in-depth knowledge and a comprehensive additional qualification within a short period of time.

The following combination modules are available for selection:

The following three modules are selected for this module combination:

  • Evidence-based medicine, knowledge representation and decision support
  • Predictive Analytics and Machine Learning
  • Signal and Image Processing

Desirable previous knowledge and interests: 

  • Basic understanding of medicine/life sciences and health sciences
  • Experience with statistics, data analysis, or programming is an advantage
  • Interest in the principles of practical application of AI in patient care, medical diagnostics, and decision support

What skills will you acquire? 

  • In this continuing education program, you will develop the ability to use ontology-based knowledge representations (e.g., SNOMED CT, UMLS) and strengthen medical decisions through evidence-based methods and modern decision support systems.
  • You will learn how to develop predictive models for patient risks, diagnostics, or therapy optimization, as well as how to model time series and multivariate clinical data using Python, R, or ML frameworks for clinical data sets. 
  • You will learn how to analyze medical image and signal data (MRI, CT, ECG, EEG) using image processing algorithms and feature engineering, as well as the practical use of OpenCV, ITK, MATLAB, or Python for image and signal analysis. 
  • This will enable you to transfer data-driven insights directly into the clinical context. 

This education program is right for you if you want to play an active role in shaping the digital transformation of medicine and are interested in translating clinical data into concrete applications for diagnostics and therapy. 

Bei dieser Modulkombination werden die folgenden drei Module gewählt

  • Data Integration and Interoperability
  • Predictive Analytics and Machine Learning
  • Bioinformatics

Desirable previous knowledge and interests: 

  • Basic knowledge of natural sciences/statistics, computer science, or medicine/life sciences
  • Experience with data analysis, databases, or programming environments (e.g., Python, R) 
  • Interest in biological and medical issues and the interaction between AI and life sciences 

What skills will you acquire? 

  • In this continuing education program, you will learn methods for linking complex and heterogeneous data sources (clinical registries, laboratory data, omics data) and converting them into interoperable data structures and making them usable through the application of standards such as HL7 FHIR or FAIR Data Principles.  
  • You will learn how to handle structured and unstructured data and develop knowledge in the development, training, and evaluation of prediction models (classical and deep learning) to derive innovative prediction models and patterns from this data.  
  • You will also expand your knowledge of bioinformatics so that you can analyze biological systems using statistical methods for big data in biomedicine and apply modern methods of systems and molecular biology.

This education program is right for you if you want to integrate biomedical data at the interface between medicine, biology, and computer science and make it usable for research or application.  

  • Duration of all modules: One semester

  • Term: Winter semester (October – March)

  • Requirements: none

  • Degree: RWTH Expert Certificate

  • Credit Points: 15 ECTS

  • Course language: English

  • Course fees: 7,490€

Individual modules – customized, focused, flexible

With our individual modules, you can delve deeper into precisely those topics that are relevant to your profession and your development—individually and flexibly.

The following individual modules are available for you to choose from:

Who is the course relevant for? 

The course is aimed at professionals who want to expand their knowledge in the field of software development and apply it specifically to medical software, who are interested in regulatory requirements such as the MDR (Medical Device Regulation) or IVDR (In-vitro Diagnostic Regulation), and who support or are responsible for software projects in the healthcare environment. 

Desirable prior knowledge
To participate in this course, you should have a basic understanding of data models, algorithms, and programming. It is also helpful to have had some initial exposure to the topic of risk management. 

What will you learn in this course?
In this course, you will learn: 

  • about different software development process models,
  • how to apply requirements analysis methods in practice,
  • the basics of software architecture and design,
  • how to classify regulatory requirements such as MDR and IVDR,
  • how to classify and qualify medical software according to regulatory requirements,
  • different testing approaches and how to apply them.

What skills will you develop?
After completing the course, you will be able to: 

  • create an Intended Use Description in accordance with MDR,
  • develop use case-based specifications,
  • derive and document test cases,
  • specify, design, and test software systems at the architectural level,
  • evaluate software in terms of usability and legal requirements,
  • create documentation in accordance with regulatory requirements.

Who is the course relevant for?
The module is aimed at specialists and managers from IT, healthcare, or related industries who want to gain a sound, practical introduction to the architecture and management of information systems and IT-supported processes in healthcare, health care, and research and  to contribute their knowledge in a targeted manner to interdisciplinary teams in order to create a  basis for secure, efficient, and sustainable IT structures. 

Desirable prior knowledge
To participate in this course, you should understand the basic principles of risk management and IT security.
A basic understanding of IT systems in healthcare and the roles and responsibilities of manufacturers, operators, and users is also helpful. 

What will you learn in this course?
In this course, you will learn: 

  • how to confidently use the technical terminology for different information systems in healthcare,
  • to understand the architecture of hospital information systems and how they interact, 
  • how to classify different IT strategies with their strengths and weaknesses,
  • the principles of IT system and service management in accordance with the ITIL®4 Foundation course 
  • relevant standards and principles of information and IT security (e.g., KRITIS, ISO 27001, ISO 80001). 
  • about the roles and responsibilities of manufacturers, operators, and users in the IT landscape 
  • how to use the 3LGM² modeling language to analyze and represent system architectures 

What skills will you develop?
After completing the course, you will be able to 

  • represent and analyze information system architectures using the 3LGM² modeling language
  • apply principles and selected methods of information system management in practice
  • take fundamental principles of information and IT security into account when planning and implementing projects
  • evaluate information systems for medical care and research with a view to integration procedures and quality aspects
  • actively participate in organizations that develop, operate, control, or are responsible for health IT services

Who is the course relevant for?
The course is aimed at managers and specialists who are interested in data science in healthcare and want to learn how to design data management and analysis processes in such a way that they are reproducible, repeatable, and reusable, while also taking into account the legal, ethical, and technical challenges involved in handling healthcare data. 

Desirable prior knowledge
To participate in this course, you should already have a basic understanding of databases, data models, and statistical methods.
Initial experience in handling medical data or research projects is also helpful. 

What will you learn in this course?
In this course, you will learn: 

  • How to create data management plans and implement the FAIR data principles in practice
  • The basics of data protection concepts (e.g., TMF data protection)
  • how to use electronic data capture (eCRF systems) and the possibilities for secondary use of health data in hospitals,
  • how to classify infrastructures for accessing medical research data (data integration centers, research data portals, research data centers),
  • how to use various data sources and types of information in biomedical research,
  • apply data exploration, pattern recognition, NLP, and validation techniques for machine learning,
  • apply methods of data ethics and data security in practice.

What skills will you develop?
Upon completion of the course, you will be able to  

  • develop data analysis approaches for specific medical questions,
  • write and apply data management plans for clinical studies,
  • create FAIR-compliant datasets using metadata,
  • apply principles of semantic interoperability and the use of ontologies in a biomedical context,
  • generate and document workflows for data science,
  • combine different methods to meet ethical, legal, and technical requirements when handling health data,
  • critically assess the strengths and limitations of routine medical data for preventive, diagnostic, and therapeutic decision-making processes.

  • Duration of a module: One semester

  • Term: Winter semester (October–March) or summer semester (April–September)

  • Requirements: none

  • Degree: RWTH Academic Certificate

  • Credit Points: 5 ECTS

  • Course language: English

  • Course fees: 2,940€

Certificate Course – Clinical Data Integration and Interoperability

Learn about the opportunities and challenges of creating, communicating, transforming and using biomedical data in our Clinical Data Integration and Interoperability certificate course. Gain valuable skills in integrating such data from different information systems and effectively using interoperability standards, and learn how to successfully implement data integration in a clinical context.

Your benefits at a glance

  • No barriers to entry – no admission requirements; you can start right away.

  • Acquire expertise quickly – concentrated learning at university level, specifically for working professionals.

  • Practical application – content is directly tailored to current challenges in healthcare and IT.

  • Maximum flexibility – take individual modules or combination modules to suit your time budget and career plan.

  • Part-time & time-saving – all modules can be completed within one semester and can be better integrated into your everyday work, allowing you to optimally combine your career and further education.

  • Career booster – recognized additional qualifications strengthen your profile and your position in your profession.

  • Optional creditability – all ECTS credits are fully transferable to a master’s program.

  • Certified continuing education – benefit from an official university certificate from RWTH Aachen University.

  • Plannable continuing education – fixed semester periods give you orientation and enable a clear structure alongside your job.

Do you have any further questions?

We will be happy to advise you personally

Antonia Mork
Study Course Manager

This course is supported by
German Association of Healthcare IT Vendors
www.bvitg.de

and
Zentrum für Telematik und Telemedizin
www.ztg-nrw.de