| COMPUTER ENGINEERING (ENGLISH, THESIS) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| BDA5012 | Big Data in Cloud Computing | Spring Fall |
3 | 0 | 3 | 8 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Assist. Prof. ECE GELAL SOYAK |
| Course Objectives: | The objective of this course is to introduce students with essential concepts of Cloud Computing and how to use them in Big Data. |
|
The students who have succeeded in this course; 1) Understand Current Cloud Computing Technologies such as Virtual Machines, SAAS, IAAS, Cloud Based Networks, Cloud Based Databases 2) Understand and articulate how to use and develop products on Cloud Computing Systems 3) Develop skills to analyse problems to create solutions using Cloud Computing and integrate this solution to Big Data Systems. |
| The course will cover topics in architectures, features, and benefits of Cloud Computing; Cloud Computing technologies such as Virtual Machines, SAAS, IAAS, Cloud Based Networks, Cloud Based Databases. Describe Cloud Computing solutions, and identify parameters for managing and monitoring big data infrastructure. Scenarios using sample data will be conducted, to develop skills using Cloud Computing Infrastructure. |
| Week | Subject | Related Preparation | |
| 1) | Course structure, resources, Cloud Computing concepts and scenarios | ||
| 2) | Virtual Machines and Understanding with the Code library, SDKs, and IDE toolkits | ||
| 3) | Service object models and baseline concepts for working with storage systems and Databases | ||
| 4) | Service object models for Notification and Queue Services | ||
| 5) | Understanding Security and Applying security features | ||
| 6) | Application Development and Deployment Best Practices | ||
| 7) | Distributed Environments | ||
| 8) | Event Driven Scaling | ||
| 9) | Orchestrating Batch Processing | ||
| 10) | Large Scale Design Patterns | ||
| 11) | Case Study 1 | ||
| 12) | Case Study 2 | ||
| 13) | Projects presentations | ||
| 14) | Project presentations | ||
| Course Notes: | Ders Notları, Referans Kaynaklar, Referans Kitaplar |
| References: | Cloud Computing: Concepts, Technology & Architecture,Thomas Erl,Prentice Hall Cloud Computing: Theory and Practice,Dan C. Marinescu, The Great Cloud Migration: Your Roadmap to Cloud Computing, Big Data and Linked Data ,Michael C. Daconta |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | % 0 | |
| Laboratory | % 0 | |
| Application | % 0 | |
| Field Work | % 0 | |
| Special Course Internship (Work Placement) | % 0 | |
| Quizzes | % 0 | |
| Homework Assignments | % 0 | |
| Presentation | % 0 | |
| Project | 1 | % 20 |
| Seminar | % 0 | |
| Midterms | 1 | % 30 |
| Preliminary Jury | % 0 | |
| Final | 1 | % 50 |
| Paper Submission | % 0 | |
| Jury | % 0 | |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 30 | |
| PERCENTAGE OF FINAL WORK | % 70 | |
| Total | % 100 | |
| Activities | Number of Activities | Workload | |
| Course Hours | 14 | 42 | |
| Laboratory | |||
| Application | |||
| Special Course Internship (Work Placement) | |||
| Field Work | |||
| Study Hours Out of Class | |||
| Presentations / Seminar | |||
| Project | 7 | 45 | |
| Homework Assignments | |||
| Quizzes | |||
| Preliminary Jury | |||
| Midterms | 5 | 25 | |
| Paper Submission | |||
| Jury | |||
| Final | 4 | 27 | |
| Total Workload | 139 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | To be able to follow scientific literature, analyze it critically and use it effectively in solving engineering problems. | |
| 2) | To be able to design, plan, implement and manage original projects related to Computer Engineering. | |
| 3) | To be able to conduct Computer Engineering related studies independently, take scientific responsibility and critically evaluate the results obtained. | |
| 4) | To be able to present the results of his/her research and projects effectively in written, oral and visual form in accordance with academic standards. | |
| 5) | To be able to conduct independent research on topics related to Computer Engineering that require specialization, to develop original ideas and to transfer this knowledge to practice. | |
| 6) | Uses advanced theoretical and practical knowledge specific to Computer Engineering effectively. | |
| 7) | Acts in accordance with professional, scientific and ethical values; takes responsibility by considering the social, environmental and ethical impacts of engineering practices. |