Computer Science & IT Study Abroad Programs in Sweden

2 Computer Science & IT Study Abroad Programs in Sweden
University Studies Abroad Consortium
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If you’re looking for a unique study abroad experience, USAC offers a program that will take you to Växjö – a town that boasts beautiful glassworks and a high-tech furniture and paper manufacturing industry amidst picturesque natural surroundings. The Växjö (pronounced Vĕck-qŭh) /Kalmar program involves enrollment in a broad range of English-taught courses at Linnaeus University’s Växjö or Kalmar campus. Both cities offer easy access to southeast Sweden’s natural environment of countryside, trails, lakes, and forests. Choose to stay for a semester or full year, taking courses in Humanities, Social Work, Computer Science, Engineering, Design, and several other disciplines. You can also take Introductory, Beginner, Intermediate, or Advanced Swedish in addition to the regular study program (included in program fees) – an ideal option for exchange students. The Introductory course is non-credited, while the other courses (Beginner, Intermediate, and Advanced) award credits. Most people in Sweden speak some English, but we strongly recommend you enroll in one of these optional courses to assimilate better into Swedish culture and way of life.
DIS - Study Abroad
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Computing is everywhere. It advances science and industry, helps us stay connected, and affects our lives at individual and societal levels. With publicly-financed specialized education, startup incubators, and industrial hubs with computer science at their core, Sweden is at the forefront of research and innovation in this field. This program is a good fit if you have an interest in: Computer Science Information Science Mathematics In this program, you focus on machine learning, which utilizes training data to develop models capable of identifying patterns, classifying large amounts of information, making predictions or decisions, and providing insights embedded in vast and complex data. This course offers a hands-on approach to the theory and practice of machine learning, with real-world applications. It focuses on training datasets, machine learning approaches, and the fitting and optimization of models.
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