Course syllabus - Big Data and Cloud Computing for Industrial Applications, 5 credits
Spring semester 2020
A1N (Second cycle, has only first-cycle course/s as entry requirements).
Product and Process Development
School of Innovation, Design and Engineering
Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.
Data science for business : [what you need to know about data mining and data-analytic thinking]
1. uppl. : Sebastopol, Calif. : O'Reilly, 2013 - xviii, 384 s.
ISBN: 9781449361327 LIBRIS-ID: 14216741
Övrigt material tillhandahålls av läraren.
The aim of this course is to provide the student with knowledge and insights in handling and processing data in the cloud environment and an understanding of the advantages and disadvantages it has in comparison with alternative solutions. The course will provide students with the necessary knowledge to understand what conditions that are required for virtually processing, storing and analyzing data. The course also gives the student basic knowledge about methods and tools for data analysis from a production and a logistic perspective.
Upon completion of the course shall the student be able to:
1. Describe the advantages and disadvantages in using cloud computing and describe the most important driving forces and obstacles for using Cloud Computing in the Manufacturing industry
2. Explain and describe different services that can be offered by different Cloud platforms
3. Describe the basic principles of machine learning and Big Data as well as describe and understand the most important prerequisites and challenges for utilization of Big Data and Machine learning within the Manufacturing industry
4. Understand and use suitable tools for analysis of manufacturing data and explain the result
5. Demonstrate the ability to practically and theoretically translate his / her knowledge within cloud services for applications in production, logistics and product development
The course contains lectures, project work, assignments and laboratory sessions where the student gets knowledge of various applications of cloud technology and management of Big Data in the manufacturing industry.
40 credits in engineering/technology and at least 2 years of work experience in full-time from relevant area within industry.
In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.
Assignment (INL1), 1 credit, marks Fail (U) or Pass (G) (examines learning outcomes 1-2)
Project (PRO1), 2,5 credits, marks Fail (U), 3, 4 or 5 (examines learning outcomes 3-6)
Laboratory work (LAB1), 1,5 credits, marks Fail (U) or Pass (G) (examines learning outcomes 4-5)
A student who has a certificate from MDH regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2016/0601). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.
Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.Study guide
Grading scale: 5, 4, 3
Interim Regulations and Other Regulations
The course overlaps 5 credits with PPU433 Cloud Based Data Management and Analytics