Are you interested in learning more about the untapped potential of spectral imaging applied to environmental systems? If so, join this course and learn how spectral imaging can be used for control and optimization of environmental technology and come up with novel application ideas that can benefit society.
This course provides an understanding of the fundamental problems in software testing, as well as solid foundation in the practical methods and tools for a systematic state-of-the-art approach to testing of software.
Statistics is vital in every field and in this course, you will learn the role it can play in the field of sustainable development. You will learn certain statistical tools, how to apply them, and ways of thinking about results that will aid you in your studies and future career.
The course will present real-world applications of control methods for energy processes and power plants. Practical considerations will be made on selecting the best control architecture and including modifications to improve control response.
In the modern IT world, businesses often have access to large amounts of data collected from customer management systems, web services, customer interaction, etc. The data in itself does not bring value to the business; we must bring meaning to the data to create value. Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data.
This course will focus on applied machine learning, where we learn what algorithms and approaches to apply on different types of data.This course is for experienced developers working in the industry. The course includes the following: Supervised learning, different types of data and data processing, Algorithms for handling text documents, Algorithms for handling data with numerical and categorical attributes, Neural Networks and Deep Learning for image recognition
The mobile and connected world of today generates a large amount of data that needs to be managed, analysed, and linked. This is often done on the cloud. The development, deployment, and management of this is called Cloud Computing. The purpose of this course is to offer a wide background about designing, developing, deploying, testing, and monitoring a cloud solution, specifically with a focus on big data problems.
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.