ADVANCED INFORMATION SYSTEM DESIGN
- Course
- ITEC550 - ADVANCED INFORMATION SYSTEM DESIGN
- 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
-
ADVANCED INFORMATION SYSTEM DESIGN
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 | Course Introduction, The Systems Development |
| Week 2 | Managing Information Systems Projects |
| Week 3 | Systems Planning and Selection |
| Week 4 | System Analysis |
| Week 5 | Design: Forms and Report |
| Week 6 | Design: Interfaces and Dialogues |
| Week 7 | Design: Interfaces and Dialogues |
| Week 8 | Midterm Week |
| Week 9 | Design: Database |
| Week 10 | Design: Database |
| Week 11 | Controling the Information Systems |
| Week 12 | Project Presentation |
| Week 13 | Project Presentation |
| Week 14 | Project Presentation |
| Week 15 | Final Exam |
Reference Books & Course Materials
- 01 Management Information Systems, MANAGING THE DIGITAL FIRM
- 02 Hoffer, et al., (2014). Modern Systems Analysis and Design, 7th Edition.
- 03 Lauron, et al(),Essential of Management Information Systems
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
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