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 |
| CMP5931 | Special Topics I | Fall Spring |
3 | 0 | 3 | 12 |
| 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 : | Assist. Prof. TARKAN AYDIN |
| Course Lecturer(s): |
Assist. Prof. TARKAN AYDIN Assist. Prof. TAYFUN ACARER Prof. Dr. SÜREYYA AKYÜZ |
| Recommended Optional Program Components: | None |
| Course Objectives: | This is a research-oriented course and designed to teach the state-of-art knowledge in various topics in computer engineering domain. There will be extensive reviews of seminal research papers in various selected topics. |
Learning Outcomes
|
The students who have succeeded in this course; |
Course Content
| Instructor's choice of a topic in Computer Engineering. |
Weekly Detailed Course Contents
| Week | Subject | Related Preparation |
| 1) | Introduction / Orientation | |
| 2) | Fundamental concepts in related topic. | |
| 3) | Selection and Distirbution of the research and presentation subjects | |
| 4) | Literature study | |
| 5) | Literature study | |
| 6) | Literature study | |
| 7) | Literature study | |
| 8) | Literature study | |
| 9) | Literature study | |
| 10) | Literature study | |
| 11) | Literature study | |
| 12) | Presentations by the students | |
| 13) | Presentations by the students | |
| 14) | Presentations by the students | |
| 15) | Presentations by the students | |
| 16) | Final Exam |
Sources
| Course Notes / Textbooks: | Seleceted reseach papers |
| References: |
Evaluation System
| Semester Requirements | Number of Activities | Level of Contribution |
| Presentation | 2 | % 50 |
| Final | 1 | % 50 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 50 | |
| PERCENTAGE OF FINAL WORK | % 50 | |
| Total | % 100 | |
ECTS / Workload Table
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Study Hours Out of Class | 14 | 8 | 112 |
| Presentations / Seminar | 2 | 6 | 12 |
| Final | 1 | 30 | 30 |
| Total Workload | 196 | ||
Contribution of Learning Outcomes to Programme Outcomes
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | To be able to follow and critically analyze scientific literature and use it effectively in solving engineering problems. | |
| 2) | To be able to design, plan, implement and manage original projects related to Big Data Analytics and Management. | |
| 3) | To be able to carry out studies on Big Data Analytics and Management independently, take scientific responsibility and critically evaluate the results obtained. | |
| 4) | Effectively present the results of his/her research and projects in written, oral and visual form in accordance with academic standards. | |
| 5) | To be able to conduct independent research in the field of Big Data Analytics and Management, develop original ideas and transfer this knowledge to practice. | |
| 6) | Uses advanced theoretical and practical knowledge specific to the field of Big Data Analytics and Management effectively. | |
| 7) | Acts in accordance with professional, scientific and ethical values; takes responsibility by considering the social, environmental and ethical impacts of engineering applications. |