| Course Type | Elective Course |
|---|
| Course Level | Master's Degree Without Thesis |
|---|
| Year of Study | - |
|---|
| Semester | - |
|---|
| ECTS | 10 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Will have broad knowledge about data management
- Are able to scan large data chunks and extract meaningful information patterns from them
- Will learn the ethical principles that must be followed in the data collection process.
- Will have knowledge of the algorithms used in the large data collection process.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | none |
|---|
| Course Description | At the end of this course students will be able to make analysis from complex and dense data sets. Also, they will be able to uncover hidden patterns and gather meaning information from hidden patterns in datasets. In this course, students will learn different data analysis methods, analytical modeling, basic optimization and statistical techniques. In this regard, this course will cover the following topics: basic data management, data mining, social network analysis, machine learning, mathematical decision models and statistical analysis. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Basic data management |
|
2nd Week |
Basic data management |
|
3rd Week |
Data mining |
|
4th Week |
Data mining |
|
5th Week |
Data mining |
|
6th Week |
Social network analysis |
|
7th Week |
Social network analysis |
|
8th Week |
Midterm |
|
9th Week |
Machine learning |
|
10th Week |
Machine learning |
|
11th Week |
Mathematical decision models |
|
12th Week |
Mathematical decision models |
|
13th Week |
Statistical analysis |
|
14th Week |
Statistical analysis |
|
15th Week |
General Review |
|
16th Week |
|
|
| Recommended or Required Reading | Lecture notes |
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Case Study
- Practice
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
40 |
| Assignment |
1 |
10 |
| Quiz |
1 |
10 |
| Total(%) |
|
60 |
| Contribution of In-term Studies to Overall Grade(%) |
|
60 |
| Contribution of Final Examination to Overall Grade(%) |
|
40 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
1 |
1 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
8 |
112 |
| Preparation for Final exam |
1 |
39 |
39 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
40 |
40 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
1 |
1 |
| Homework |
5 |
11 |
55 |
| Quiz |
1 |
10 |
10 |
| Total Work Load | 300 |
| Total Work Load / 30 (h) | 10 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
|---|
| Work Placement(s) | No |
|---|
