Within the field of software engineering and computer science, we offer tree courses - below, you will find more information about each course.
Please check the individual course descriptions for possible prerequisites and remember to see at which campus it is offered.
Artificial Intelligence for Healthcare Data
Every day, a massive amount of patient data is generated and recorded on a global scale. Artificial Intelligence (AI) has the power to automatically process all this complex data and use it to improve the accuracy and quality of healthcare services, and to generate innovative solutions in this sector. It can therefore be used in a variety of settings and disease conditions for e.g., the improvement of diagnosis and treatment decisions, prediction of clinical outcomes, patient monitoring and development of medical devices. This course will introduce students to the fundamentals and applications of AI in the healthcare environment, by offering the chance of working with different types of health data, such as structured patient journals, medical imaging results, and time-series. Techniques used to handle health data, as well as selective AI algorithms suited for the problems, will be explored across real-life challenges within the healthcare setting. Focus will be given to supervised machine learning algorithms, e.g. classification, regression.
Continuous Delivery and DevOps
During the course you will learn to apply software engineering practices and tools from professional software developers. The course in Software Delivery and DevOps is organized by Praqma and SDU and you will get tips and tricks on how to use Git, Docker, Jenkins and more. After completing the course you will be able to: 1. Construct a continuous delivery pipeline and apply it on a small software project, 2. Apply professional tools for build, test, and deployment automation, 3. Demonstrate DevOps mindset, 4. Compare Continuous Delivery and DevOps with other software engineering approaches, describe their prerequisites, benefits and barriers, 5. Explain how continuous delivery can support innovation experiments and value creation.
Machine learning has become a part in our everyday life, from simple product recommendations to personal electronic assistant to self-driving cars. Especially deep learning has gained a lot of interest in the media and has demonstrated impressive results. This intensive course will introduce you to the exciting world of deep learning. We will learn about the theoretical background and concepts driving deep learning and highlight and discuss the most noteworthy applications of deep learning but also their limitations. Furthermore you will also apply and implement your first deep neural networks in order to solve various interesting machine learning tasks.