COMPUTER ENGINEERING (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 Spring |
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 : | Prof. Dr. ADEM KARAHOCA |
Course Lecturer(s): |
Prof. Dr. ADEM KARAHOCA |
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) | Define and manipulate advanced concepts of Computer Engineering | |
2) | Use math, science, and modern engineering tools to formulate and solve advenced engineering problems | |
3) | Notice, detect, formulate and solve new engineering problems. | |
4) | Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results | |
5) | Follow, interpret and analyze scientific researches in the field of engineering and use the knowledge in his/her field of study | |
6) | Work effectively in multi-disciplinary research teams | |
7) | Acquire scientific knowledge | |
8) | Find out new methods to improve his/her knowledge. | |
9) | Effectively express his/her research ideas and findings both orally and in writing | |
10) | Defend research outcomes at seminars and conferences. | |
11) | Prepare master thesis and articles about thesis subject clearly on the basis of published documents, thesis, etc. | |
12) | Demonstrate professional and ethical responsibility. | |
13) | Develop awareness for new professional applications and ability to interpret them. |