BIG DATA AND CLOUD COMPUTING FOR INDUSTRIAL APPLICATIONS

In this course, you will gain insight in components and technologies included in the Industrial Internet of Things (IIoT). Designed specifically for manufacturing sector professionals, the course provides knowledge about the infrastructure, the technologies and requirements needed to generate, transport and manage data in the Industrial Internet of Things (IIoT) system which is one of the main building blocks towards digitalization and smart factories. It includes project work, laboratory exercises and assignments where the student gets knowledge of different applications of IIoT in the manufacturing industry.

Do you want to be efficient, effective and minimize waste by learning and implementing lean production tools? This course provides insight into the demands and challenges posed by competitive production in industrial production systems and develops your ability to participate in and to drive improvement work. The course focuses on efficient lean production. Through theory and project work, you will learn useful techniques, methods and strategies. You will obtain the necessary knowledge and training to carry out value stream mapping and other forms of improvement work. The course offers current and competitive knowledge through its close links with our successful research and partner companies. It provides basic knowledge and understanding of the modern view of lean production in industrial activity. 

Participants in this master course will develop skills in discrete event simulation to meet the needs of today's manufacturing industry. Through use of discrete event simulation you will learn to support improvements of industrial processes involving complex changes. The course focuses on how to build, analyse and communicate the results of a simulation study. You will acquire knowledge through theoretical understanding, practical exercises and workshops. Based on a real case, the course will guide you to be able to improve production and logistics flow with discrete event simulation.

Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML). The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.

Modern web applications can often be described in terms of cooperation and sharing, both on the level of the users of the application and on the level of the application and the service providers. This course covers the most prevalent security challenges of web applications, from a theoretical and practical perspective.  

The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling