Course syllabus - Smart Digital Platforms: Cloud Computing, Security and Big Data

Objectives

The purpose of this course is to introduce the concept of cloud computing and give knowledge and insights in handling and processing Big Data in the cloud. The course will provide students with the necessary theoretical and practical knowledge to be able to use cloud services in managing Big Data and taking into account the data security aspects.

Learning outcomes

After completing the course, the student shall be able to:
 
1. describe the cloud models, service models, structure and functionalities,
2. describe the concept of Big Data and relation to cloud services,
3. differentiate between different database services and apply them in different scenarios,
4. understand and compare different storage options,
5. describe and recommend how data is secured in cloud environment and
6. practically apply a number of cloud services to search large amounts of data.

Course content

- Introduction to Cloud Computing: Concept, Architecture, Services, and Deployment models
- Cloud technologies: Virtualization, Load Balancing, Scalability and Elasticity
- Cloud storage: Overview of storage technologies
- Cloud databases: Database concept and languages
- Big Data in the cloud: Concept and analytic services
- The de facto Big Data processing frameworks: Hadoop and MapReduce
- Security and Privacy in the cloud: Concept and challenges
- Cloud Access: authentication, authorization and accounting

Specific requirements

Programming 7,5 credits.

Examination

Written examination (TEN1), 2,5 hp, examines the learning outcomes 1-5, marks Fail (U), 3, 4 or 5.
Project  (PRO1), 3 hp, examines the learning outcome 6, marks Fail (U), 3, 4 or 5.
Laboratory work (LAB1), 2 hp, examines the learning outcomes 2-4, marks Fail (U) or Pass (G).

A student who has a certificate from MDU 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 (2020/1655). 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.

Grade

Pass with distinction, Pass with credit, Pass, Fail

Interim Regulations and Other Regulations

The course overlaps with 3 credits towards DVA453 Machine Learning with Big Data, with 4.5 credits towards DVA254 Cloud Services and with 2.5 credits towards DVA444 Industrial Systems in Cloud Computing.