​​FCLF1-CC30​ ​Cloud Computing

​​FCLF1-CC30​ ​Cloud Computing

  • Course description
    • Course code
      ​​FCLF1-CC30​
    • Level of study
      5.1
    • Program of study
      Cloud Foundations
    • Credits
      30
    • Course coordinator
      Kristoffer Thomsen
Teaching term(s)
2024 Autumn
2025 Spring
About the Course

About the Course 

​​The course provides knowledge of cloud computing and skills to configure solutions based on project specifications. Cloud computing is renting resources, like storage space or CPU cycles, instead of running them on their own equipment. Candidates are provided knowledge and skills to work with important elements such as rapid development cycle, try/fail, pay as you go, scalability and elasticity. The course is based on Microsoft Azure; however, the theory, concepts and terminology are standard among the major vendors. 

​To master data in the cloud, you need the right foundation—a solid understanding of core data concepts, such as relational data, nonrelational data, big data, and analytics. Plus, familiarity with data and data analytics roles, tasks, and responsibilities. 

​Whether you’re a beginning technical professional, student, or business user, this course will offer knowledge of the business value and product capabilities of Microsoft Azure. The course will also provide insights into foundational knowledge of cloud-based solutions to facilitate productivity and collaboration on-site, at home, or a combination of both. 

​The course aims to provide fundamental competence to utilise cloud services securely. As the demand for increased performance storage requirements increases, and the lines between on-premises computing versus cloud computing become more diffuse, many businesses are moving fast toward cloud computing, and the need for competent personnel is also increasing. 

​This course offers the foundation to build your technical skills to start working with services in the cloud. Mastering the basics can help you jump-start your career and prepare you to dive deeper into other technical opportunities in the cloud. 

Course Learning Outcomes
Learning outcomes - Knowledge

The candidate:  

  • ​​has knowledge of concepts, processes and tools that are commonly used in cloud computing.  
  • ​has knowledge of processes, limitations and management of on-premises and cloud environments.  
  • ​has knowledge of cloud concepts and services offered through Microsoft Power Platform and 365. 
  • ​has knowledge of security, compliance, identity, privacy, and trust in Microsoft Azure and 365. 
  • ​has knowledge of structured, unstructured, and semi-structured data. 
  • ​has knowledge of Microsoft Azure Active Directory. 
  • ​has knowledge of security, compliance, identity, and governance concepts. 
  • ​has insight into relevant regulations, standards, agreements and quality requirements regarding cloud computing, cloud providers and Azure resources. 
  • ​has insight into relevant regulations, standards, agreements, and quality requirements related to Microsoft 365.  
  • ​can update their knowledge about cloud computing, concepts, and services.  
  • ​can update their own knowledge about Azure resources, such as storage, virtual networking, and compute. 
  • ​understands the importance of security and integrity of cloud environments from a societal perspective. ​ 
Learning outcomes - Skills

The candidate: 

  • ​​can apply knowledge of cloud-based technology to connect and interact with and between systems. 
  • ​can apply knowledge of core data concepts to represent structured, semi-structured and unstructured data. 
  • ​can apply knowledge to working with non-relational and relational data in the cloud. 
  • ​can apply knowledge to deploy and manage Azure storage, virtual networks, and compute resources. 
  • ​can apply knowledge of Microsoft 365 to describe productivity, collaboration, access management and threat protection solutions. 
  • ​can apply knowledge of Microsoft Power Platform to demonstrate the capabilities of Power Apps. 
  • ​masters relevant tools and techniques to interact with and configure cloud computing systems and services. 
  • ​can describe relational and non-relational concepts and considerations in real-time data analytics. 
  • ​can describe the capabilities of Microsoft identity, access management, security, and compliance solutions. 
  • ​can find information and material relevant to maintaining and troubleshooting cloud-based services. 
  • ​can find information and material that is relevant to core data concepts and analytics workloads in the cloud. 
  • ​can find information and material that is relevant to Microsoft 365 apps and services. 
  • ​can study a cloud-based environment and identify issues in cloud computing and what measures need to be implemented.​ 
General Competence

The candidate:  

  • ​​has developed an ethical attitude in relation to the access of data that is common when working with cloud-based systems. 
  • ​can carry out work on cloud-based systems based on the needs of selected users. 
  • ​can carry out work on data services in the cloud based on the needs of selected users. 
  • ​can carry out work on Power BI and Power Apps based on the needs of selected users. 
  • ​can implement and manage Azure identities, governance, storage, virtual networking, and compute resources. 
  • ​can monitor and maintain Azure resources. 
  • ​can develop work methods, products and/or services relevant to the administration of cloud services. 
  • ​can develop work methods, products and/or services relevant to storage, virtual networks, and compute resources. 
  • ​can develop work methods, products and/or services relevant to Azure identities, governance, and compute resources. 
  • ​can develop work methods, products and/or services relevant to Microsoft Power Platform and the Microsoft 365 apps and services
Teaching and Learning

In this course, the following teaching and learning methods can be applied, but are not limited to:

  • Lecture: Educator-led presentations or activities providing knowledge, skills, or general competencies in the subject area.
  • Group work: Collaborative activities where students work together to solve problems or complete tasks.
  • Tutoring: One-on-one or small group sessions with an instructor for personalized guidance and support.
  • Student presentations: Opportunities for students to demonstrate their understanding of course material by presenting to peers.
  • Online lessons: Digital content delivered via an online learning platform.
  • Guidance: Individualized advice and direction from instructors to support students in their learning journey.
  • Workshops: Practical sessions focused on hands-on application of theoretical concepts or skills.
  • Self-study: Independent study where students engage with course material on their own without any teacher support.
Reading list

Teaching materials, reading lists, and essential resources will be shared in the learning platform and software user manuals where applicable.

Work requirements and Assessment

Four (4) mandatory work requirements must be submitted throughout the semester in addition to the Semester Project submission. The four mandatory work requirements will be assessed as Pass/Fail. 

Assessments
Form of assessmentGrading scaleGroupingDuration of assessment
Semester Project
Grade A-F
Individual
19 Week(s)