BAHÇEŞEHİR UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| BIG DATA ANALYTICS AND MANAGEMENT (ENGLISH, NONTHESIS) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
Course Introduction and Application Information
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| BDA5012 | Big Data in Cloud Computing | Fall | 3 | 0 | 3 | 8 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Basic information
| Language of instruction: | English |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi SERKAN AYVAZ |
| 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. |
Learning Outcomes
|
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. |
Course Content
| 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. |
Weekly Detailed Course Contents
| 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 |
Sources
| Course Notes / Textbooks: | 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 |
Evaluation System
| Semester Requirements | Number of Activities | Level of Contribution |
| Project | 1 | % 20 |
| Midterms | 1 | % 30 |
| Final | 1 | % 50 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 30 | |
| PERCENTAGE OF FINAL WORK | % 70 | |
| Total | % 100 | |
Contribution of Learning Outcomes to Programme Outcomes
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution |