Computer Science – Software Technology II, Course Package

This course package comprises four courses aimed at developing and strengthening students' knowledge, skills, and expertise in parallel computing, machine learning, deep machine learning, and a degree project.

The first course, Parallel Computing, advances students' knowledge of using multiple processors and memory hierarchies to tackle computationally intensive problems. Students learn how to decompose a problem, how to formulate parallel algorithms, and how a program can be optimized for parallel processors and accelerators.

The second course, Machine Learning, provides an overview of the different areas of artificial intelligence focusing on machine learning. After completing the course, students shall be able to explain the fundamental principles, benefits, and drawback of different machine learning techniques or algorithms, select an appropriate alogrithm, and implement it to solve typical machine learning tasks.

The third course, Deep Machine Learning, will build on the foundational knowledge you have gained in the Machine Learning course. It covers concepts and methods from neural networks and deep learning. After completing the course, students are expected to describe the foundation and applications of deep learning and implement deep learning-based solutions to address problems such as image and speech recognition.

Finally, in the Degree Project course, students apply newfound skills and knowledge to a research project within the area of computer science. Students work under the guidance of a supervisor to define research questions, select an appropriate method to design and implement a project, and analyze the project results to answer the research questions. The course allows students to demonstrate their creativity, critical thinking, and problem-solving skills.

Overall, the Master's level course package offers a learning experience that prepares students to establish and strengthen their careers in rapidly evolving fields of parallel computing and machine learning.

Join the course package and embark on a fulfilling and rewarding future!

Here you will have five minutes’ walking distance to friends, restaurants, lecture rooms, gym, grocery store, the University Library, nature trails, and student pubs. If you live in another part of Växjö, you can quickly get to the university by bus or bicycle.

With its 90 000 inhabitants, Växjö is one of the fastest growing cities in Sweden. Here you will find the famous Småland entrepreneurship spirit and a lot of companies, for instance within the IT industry – perfect for when you are looking for an internship position or a job. Växjö is also a picturesque city where you are always close to forests and water.

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