| 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;
- Know a wide range of data analytics techniques (descriptive analytics, inferential analytics, and predictive analytics).
- Master different data analysis problems encountered in applications with heavy data use.
|
| Mode of Delivery | Face to face |
| Prerequisites | No |
| Recommended Optional Programme Components | Data Science |
| Course Description | Data Analytics is the science of analyzing data to convert information to useful knowledge. This knowledge could help us to make better decisions. This course aims to present you with a wide range of data analytic techniques (descriptive, inferential, predictive, and prescriptive analytics). |
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Basic Definitions: Data, Information, Value of Data, Data Analysis |
|
2nd Week |
Inferential Data Analysis |
|
3rd Week |
Descriptive Data Analysis |
|
4th Week |
Survival Analysis |
|
5th Week |
Social Network Data Analysis |
|
6th Week |
Data Analysis Processes |
|
7th Week |
Data Analysis Processes |
|
8th Week |
Mid-term Examination |
|
9th Week |
Ethical and Legal Issues |
|
10th Week |
Social Network Modeling |
|
11th Week |
Terabyte Scaled Image Analysis Applications |
|
12th Week |
Big Data Analysis Between Web Sites |
|
13th Week |
Case Study Presentations |
|
14th Week |
Case Study Presentations |
|
| Recommended or Required Reading | Inferential Data Analysis: Hypothesis Testing and Decision-Making, Tyrone Pretorius.
Descriptive Data Analysis and Statistics. Klaus Krickeberg, Van Trong PhamThi My Hanh Pham, Springer.
|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Discussion
- Problem Solving
|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
25 |
| Assignment |
3 |
30 |
| Total(%) |
|
55 |
| Contribution of In-term Studies to Overall Grade(%) |
|
55 |
| Contribution of Final Examination to Overall Grade(%) |
|
45 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
3 |
3 |
| Preparation for Quiz |
|
|
|
| Individual or group work |
14 |
7 |
98 |
| Preparation for Final exam |
1 |
50 |
50 |
| Course hours |
14 |
3 |
42 |
| Preparation for Midterm exam |
1 |
45 |
45 |
| Laboratory (including preparation) |
|
|
|
| Final exam |
1 |
3 |
3 |
| Homework |
3 |
15 |
45 |
| Total Work Load | 286 |
| Total Work Load / 30 (h) | 9.53 |
| ECTS Credit of the Course | 10 |
|
| Language of Instruction | Turkish |
| Work Placement(s) | No |