COMPUTER NETWORKS AND COMMUNICATIONS
- Course
- ITEC530 - COMPUTER NETWORKS AND COMMUNICATIONS
- Department
- Information Technologies - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
- Keywords
- -
Course Description
-
COMPUTER NETWORKS AND COMMUNICATIONS
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 - COMPUTER NETWORKS AND THE INTERNET |
| Week 2 | AAPPLICATION LAYER |
| Week 3 | TRANSPORT LAYER |
| Week 4 | THE NETWORK LAYER: DATA PLANE |
| Week 5 | THE NETWORK LAYER: CONTROL PLANE |
| Week 6 | THE LINK LAYER AND LANS |
| Week 7 | REVISION |
| Week 8 | MIDTERM EXAM |
| Week 9 | WIRELESS AND MOBILE NETWORKS |
| Week 10 | SECURITY IN COMPUTER NETWORKS |
| Week 11 | OPERATIONAL SECURITY: FIREWALLS AND INTRUSION DETECTION SYSTEMS |
| Week 12 | MULTIMEDIA NETWORKING |
| Week 13 | REVISION |
| Week 14 | FINAL EXAM |
| Week 15 | - |
Reference Books & Course Materials
- 01 Computer Networking A Top-Down Approach SEVENTH EDITION - Kurose Ross
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.
Po-Lo Matrix
The PO-LO matrix has not been populated yet.