Machine learning helps people to work more efficiently, faster and more creatively. In the last ten years, machine learning has enabled us to develop self-driving cars, speech and image recognition, effective web searches and a much better understanding of the human genome, among other things.
Machine learning can be applied wherever patterns are present in data. With the help of self-learning algorithms, patterns and regularities are recognized and solutions for new and known problems are found independently. This makes it possible, for example, to carry out data-based optimizations in product and process development or to predict customer behaviour.
In this ONLINE course, you will learn about the most effective machine learning techniques and how to implement them. You will not only learn the theoretical foundation courses, but also the practical know-how to apply these techniques quickly and effectively to new problems.

This course is held in English.

Upon successful completion of the ONLINE course, you will be able to:

• Master the foundation courses of the Python programming language.
• Prepare data so that it can be analyzed using machine learning. This includes: replacing missing data, transforming data, detecting outliers, and reducing data effectively.
• Generate predictive models for continuous (regression) and discrete (classification) as well as time-dependent target variables.
• Evaluate and improve the accuracy of the predictive model.
• Solve complex optimization problems on the predictive models in the most efficient way.
• To identify the most important influencing parameters on entrepreneurial target variables.

• Conveying the foundation course and a basic intuition for the possibilities of machine learning as a prerequisite for profitable use in the company.
• Practical relevance and professional usability of the taught contents.
• Maximum knowledge gain from your data.
• Potential resource savings (material, time, capacities, etc.).
• Easy adaptation of the teaching material for new, own tasks.
• Individual support and intensive exchange in small groups.

The course is primarily aimed at employees from product management and development engineering in the fields of technology, research and development from aerospace, mechanical engineering informatics, production and logistics, process engineering, processing technology, energy technology, automotive engineering, who want to quickly and efficiently analyze data and create predictive models, for example, to cost-effectively optimize products and processes.

The interactive seminar-style ONLINE course offers the opportunity to address individual questions and problems of the participants. Diverse use of media, small group work, practical work on the computer and the support of an online learning platform support the learning success.

The certificate course, which has an interactive seminar character, is divided into ONLINE presentations and self-learning phases. It is characterized by a mix of short impulse lectures, exercises, small group work, discussion and case studies. Online materials support the self-learning phase. Due to the limited number of participants, individual problems and questions can be addressed.

The curriculum and further information can be found in the flyer and in the download area.

• Dates: Six days of attendance upon request at weiterbildung(at)hsnr.de.
• Max. Number of participants: 12 persons
• Location: Krefeld South Campus

• Participation fee: 1.590 € | Alumni (5 % discount) 1.510 €
• Participation requirements: University degree with one year of professional experience or professional training and at least three years of professional experience. Prior knowledge of Python is an advantage, but not mandatory. You will need an internet-enabled PC or notebook for Zoom as a video conferencing service, as well as a headset if necessary. Mandatory is the ability to install and run programs.
• Scope (workload): 75 h, of which 40 h attendance, 3 ECTS.
• Degree: University certificate / certificate of attendance