SEMINAR
- Course
- BASC590 - SEMINAR
- Department
- Electronics and Communication Engineering - English - Master
- Course Type
- Seminar
- Status
- Required
- Language
- English
- Credit
- 0
- ECTS
- 0
- T+P+L
- 0 + 0 + 0
- Course Coordinator(s)
- Asst. Prof. Dr. Ali SHEFIK
- Prerequisite
- -
- Keywords
- -
Course Description
Seminar course is designed to promote research interest in various areas of Electrical and Electronic Engineering. Students are expected to further advance and deepen their knowledge regarding research methods through discussions of research results made in their fields of specialization. Students will make presentations on the progress of their research and will hold discussions with teachers to expand the range of their research. An additional objective of the research seminars is to nurture global IT specialists by having students make presentations at national or international conferences. Students are required to attend both research seminars and conferences for developing their research ability. Master students must register and fulfill departmental requirements of the seminar.
SEMINAR
Evaluation Tools (Active Term)
No evaluation items have been defined.
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction to Knowledge Management |
| Week 2 | On the Way to a Knowledge Society |
| Week 3 | Knowledge in Organisations |
| Week 4 | Strategies for Managing Knowledge |
| Week 5 | How can IS Support Knowledge Work |
| Week 6 | Crystallizing Knowledge |
| Week 7 | Revision |
| Week 8 | Midterm(s) |
| Week 9 | Midterm(s) |
| Week 10 | Constructing Knowledge Valley |
| Week 11 | Measuring and Safeguarding Intellectual Capital |
| Week 12 | Factors that stop innovation |
| Week 13 | Presentations |
| Week 14 | Revision |
| Week 15 | Final Exams |
Reference Books & Course Materials
No reference books have been listed.
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- Demonstrate a thorough understanding of the theories, frameworks, and models in order to assess and comprehend the state of the art in data science.
- Review the literature and apply data science theories and methodology in new research and experiments.
- Analyze datasets using supervised and unsupervised machine learning techniques.
- Design, develop and test statistics and informatics software systems for data management, analysis and problem solving.
- Conceptualize and develop efficient visuals for a range of data types and analytical tasks, and carry out independent research on a range of theoretical and applied subjects in visualization and visual analytics.
- Obtain a high level of proficiency in communication, problem solving, research or project-related activities and function effectively as a team member or a leader to accomplish a common goal in a multidisciplinary team.
- Develop and implement optimal solutions to overcome challenges associated with managing large datasets by utilizing parallel methods, cloud computing, and non-relational data storage and retrieval (NoSQL).
- Demonstrate an understanding of the interdisciplinary of data, information, and communications, as well as the ability to evaluate the leading research methods for data collection and analysis.
- Demonstrate a deep understanding of the ethical issues surrounding the use of data and apply ethical decision making in real-world data-related applications.
- Demonstrate capability of analyzing, synthesizing, and evaluating knowledge from a wide range of fields and be capable of lifelong self-directed learning.
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