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DURATION20 WEEKS
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SUBJECT AREASoftware Engineering
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COURSE LEVELFirst Cycle
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CREDITS7.5 HP
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INSTITUTIONMälardalen University
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STUDY TYPEDistance
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START DATE2023-08-28
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END DATE2024-01-14
COURSE DESCRIPTION
This course will provide a basic theoretical and practical knowledge in the art of configuring and securing computer networks and create simpler topologies.
Together with the "Computer Networks II" distance course (Datakommunikation i nätverk II, distanskurs) you will be covering most, but not all, of the content that are part of a Cisco Certified Network Associate (CCNA) certificate. The certificate is not part of this course.
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This course makes you acquainted with the concept of systems-of-systems (SoS), which means that independent systems are collaborating. It gives you an understanding why SoS is an important topic in the current digitalisation and provides a theoretical and practical foundation for understanding important characteristics of SoS. It also gives you a deeper knowledge in a number of key concerns that need to be considered when engineering SoS. Admitted students to this course may join the course any time between August 28 and October 6, 2023. With the recommended study pace of 25%, the course would take approximate seven calendar weeks to complete. Higher or lower study pace is possible as long as the course is finished no later than January 14, 2024.
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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
The rapid development of digital technologies and advances in communications have led to gigantic amounts of data with complex structures called ‘Big data’ being produced every day at exponential growth. The aim of this course is to give the student insights in fundamental concepts of machine learning with big data as well as recent research trends in the domain. The student will learn about problems and industrial challenges through domain-based case studies. Furthermore, the student will learn to use tools to develop systems using machine-learning algorithms in big data.
This course will teach you how to build convolutional neural networks. You will learn to design intelligent systems using deep learning for classification, annotation, and object recognition.