VBM674 - CLOUD COMPUTING and VIRTUALIZATION

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
CLOUD COMPUTING and VIRTUALIZATION VBM674 Any Semester/Year 3 0 3 6
PrequisitesNone
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesPreparing and/or Presenting Reports
Problem Solving
Project Design/Management
 
Instructor (s)To be determined by the institute 
Course objectiveTo teach the concepts of cloud computing and virtualization. 
Learning outcomes
  1. In the end of this course the student will
  2. ? Understand the cloud computing logic.
  3. ? Learn the basics of cloud computing security.
  4. ? Get information about similar methods like grid computing.
Course ContentCloud computing and web, Cloud computing and security, Data and result relation, Cloud computing sevices. 
References? George Reese, Cloud Application Architectures: Building Applications and Infrastructure in the Cloud, O'Reilly, 2009
? Toby Velte, Anthony Velte, Robert Elsenpeter, Cloud Computing, A Practical Approach, McGraw-Hill Osborne, 2009
 

Course outline weekly

WeeksTopics
Week 1Introduction to course
Week 2Cloud Computing and Web
Week 3Cloud Computing and Web(continued)
Week 4Cloud Computing and Security
Week 5Cloud Computing and Security(continued)
Week 6Case Study
Week 7Data and Result Relation
Week 8Midterm exam
Week 9Cloud Computing Services
Week 10Cloud Computing Services(continued)
Week 11Project
Week 12Report Presentation
Week 13Report Presentation
Week 14Report Presentation
Week 15Report Presentation
Week 16Final exam

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments00
Presentation110
Project130
Seminar00
Midterms120
Final exam140
Total100
Percentage of semester activities contributing grade succes060
Percentage of final exam contributing grade succes040
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 3 42
Laboratory 0 0 0
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)10330
Presentation / Seminar Preparation12020
Project13030
Homework assignment000
Midterms (Study duration)12020
Final Exam (Study duration) 13030
Total Workload28106172

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Has detailed knowledge about data and knowledge engineering (DKE).   X 
2. Has a good understanding of common concepts such as abstraction, complexity, security, concurrency, software lifecycle and applies their expertise to the effective design, development and management of IS.    X
3. Understands the interaction of theory and practice and the links between them.    X
4. Has the ability to think at different levels of abstraction and detail; understands that an IS can be considered in different contexts, going beyond narrowly identifying implementation issues.   X 
5. Solves any technical or scientific problem independently and presents the best possible solution; has the communication skills to clearly explain the completeness and assumptions of their solution.  X  
6. Completes a project on a larger scale than an ordinary course project in order to acquire the skills necessary to work efficiently in a team.   X 
7. Recognises that the field of DKE is rapidly evolving. Follows the latest developments, learns and develops skills throughout their career.  X  
8. Recognises the social, legal, ethical and cultural issues related to DKE practice and conduct professional activities in accordance with these issues.  X  
9. Can make oral presentations in English and Turkish to different audiences face-to-face, in writing or electronically.   X 
10. Recognises that DKE has a wide range of applications and opportunities.    X
11. Is aware that DKE interacts with different fields, can communicate with experts from different fields and can learn necessary field knowledge from them.   X 
12. Define a research problem and use scientific methods to solve it.    X 

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest