| BIG DATA ANALYTICS AND MANAGEMENT (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 |
| BDA5888-1 | Master Thesis | Fall | 0 | 0 | 0 | 20 |
| Language of instruction: | English |
| Type of course: | Must Course |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Assist. Prof. ECE GELAL SOYAK |
| Course Objectives: | Within the scope of this course, it is planned to conduct literature research, project analysis and design of the master's thesis to be prepared. |
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The students who have succeeded in this course; Students who successfully complete this course will be able to; I. To be able to define a problem for a scientific study. II. To be able to make a literature review in preparation for a scientific study. III. Identify research opportunities by analyzing the studies in the literature. IV. Determine the requirements that will form the basis of the scientific study. V. To analyze the methodologies to be used for the determined research topic. VI. To design the problem solution in line with the methodologies to be used. |
| Week 1 Problem definition Week 2 Problem definition Week 3: Reviewing the literature on the identified problem Week 4: Reviewing the literature on the identified problem Week 5: Reviewing the literature on the identified problem Week 6: Reviewing the literature on the identified problem Week 7: Evaluation of the studies obtained Week 8: Evaluation of the studies obtained Week 9: Analyzing the requirements for the defined problem Week 10: Analyzing the requirements for the defined problem Week 11: Analyzing the requirements for the defined problem Week 12: Analyzing the requirements for the defined problem Week 13: Designing the problem solution for the defined problem Week 14: Designing the problem solution for the defined problem |
| Week | Subject | Related Preparation |
| Course Notes / Textbooks: | |
| References: |
| Semester Requirements | Number of Activities | Level of Contribution |
| Presentation | 1 | % 100 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 100 | |
| PERCENTAGE OF FINAL WORK | % | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 16 | 3 | 48 |
| Study Hours Out of Class | 16 | 10 | 160 |
| Presentations / Seminar | 1 | 300 | 300 |
| Total Workload | 508 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | 1. To be able to follow and critically analyze scientific literature and use it effectively in solving engineering problems. | 5 |
| 2) | To be able to design, plan, implement and manage original projects related to Big Data Analytics and Management. | 5 |
| 3) | To be able to carry out studies on Big Data Analytics and Management independently, take scientific responsibility and critically evaluate the results obtained. | 5 |
| 4) | Effectively present the results of his/her research and projects in written, oral and visual form in accordance with academic standards. | 5 |
| 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. | 5 |
| 6) | Uses advanced theoretical and practical knowledge specific to the field of Big Data Analytics and Management effectively. | 5 |
| 7) | Acts in accordance with professional, scientific and ethical values; takes responsibility by considering the social, environmental and ethical impacts of engineering applications. | 5 |