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Big Data, Machine learning and Sensors

Big Data, Machine learning and Sensors

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This area provides a knowledge for Digital Transformation toward Smart Manufacturing for Industries

The module on “Big Data, Machine Learning and Sensors” is a three-chapter story that covers the main theoretical and practical aspects needed to know for Digital Transformation toward Smart Manufacturing.

The module consists of Data Sciences for Engineers, Artificial intelligence for Engineering Applications, and Digitalization of Industrial Processes.

The Data Sciences chapter presents the basics of data types and processing, neural networks, signal, and image processing related to engineering tasks.

The Artificial Intelligence for Engineering Applications chapter shows how machine learning, computer vision, and data mining can be used for engineering applications.

The last chapter Digitalization of Industrial Processes demonstrates the usage of machine learning, signal and image processing can be implemented in diagnostics, quality control, and process dynamics.

Available modules
Learning outcome
Achieve a deeper understanding and competence in Data Processing including Statistics, Image Processing, Signal Processing, and Neural Networks.
Achieve a deeper understanding of the role of Data Science in engineering.
Obtain knowledges on the data collection and analysis with focus on engineering applications.
Obtain knowledge and skills in using data processing techniques applicable to engineering tasks.
Achieve an understanding of the principles of Machine Learning and Neural Networks
Obtain knowledge of specifics of process dynamics and data mining
Obtain knowledge of principles of sensors and data acquisition systems toward AI
Obtain knowledge of basics of Computer Vision and AI for metrology
Obtain understanding of Digitalization concepts of Industrial Processes.
Obtain knowledge in pricioles of Signal Processing for Process Monitoring related to manufacturing processes.
Achieve knowledge of realization of automatic quality control for industrial applications.
Partners
Lund university
Halmstad university
Mälardalen university
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