| CYBER SECURITY (ENGLISH, NON-THESIS) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| SEN5550 | Business Intelligence | Fall | 3 | 0 | 3 | 8 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
| Language of instruction: | English |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | |
| Recommended Optional Program Components: | None |
| Course Objectives: | Participants will describe the usage based on business intelligence, data mining, business intelligence methods will contribute, open-source and commercial develop business intelligence solutions, and application will be introduced. |
|
The students who have succeeded in this course; 1. Explain the concept of Business Intelligence 2. Increase dominance reporting tools 3. Describe the contributions of Data mining 4. Define how to use basic ETL tools. |
| The content of this course is composed of introduction to business intelligence, database management systems, data warehouse models and architectures, data mining, preprocessing, driven methodology, guided algorithms and non-guided algorithms. |
| Week | Subject | Related Preparation |
| 1) | Introduction to Business Intelligence | |
| 2) | Database management systems – 1 | |
| 3) | Database management systems – 2 | |
| 4) | The data warehouse models and architectures - the application | |
| 5) | Data warehouses Datamarts | |
| 6) | Data Mining - 0 (preprocessing) | |
| 7) | Data Mining - 0 (preprocessing) / Midterm | |
| 8) | Data Mining - 1 (driven methodology and algorithms) | |
| 9) | Data Mining - 2 (Guided algorithms continued) | |
| 10) | Data Mining - 3 (non-guided algorithms) | |
| 11) | Project Presentations – 1 | |
| 12) | Project Presentations – 2 | |
| 13) | Project Presentations – 3 | |
| 14) | Overall assessment and closing |
| Course Notes / Textbooks: | Business Intelligence: Making Better Decisions Faster by Elizabeth Vitt, Michael Luckevich, Stacia Misner (2002) |
| References: | Yok |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | 14 | % 5 |
| Homework Assignments | 2 | % 10 |
| Project | 1 | % 20 |
| Midterms | 1 | % 25 |
| Final | 1 | % 40 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Application | 14 | 3 | 42 |
| Study Hours Out of Class | 14 | 3 | 42 |
| Midterms | 1 | 22 | 22 |
| Final | 1 | 41 | 41 |
| Total Workload | 189 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Understand and implement advanced concepts of Siber Security | |
| 2) | Use math, science, and modern engineering tools to formulate and solve advenced siber security problems. | |
| 3) | Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results. | |
| 4) | Follow, interpret and analyze scientific researches in the field of engineering and use the knowledge in his/her field of study. | |
| 5) | Work effectively in multi-disciplinary research teams. | |
| 6) | Acquire scientific knowledge | |
| 7) | Find out new methods to improve his/her knowledge | |
| 8) | Effectively express his/her research ideas and findings both orally and in writing | |
| 9) | Defend research outcomes at seminars and conferences | |
| 10) | Demonstrate professional and ethical responsibility. |