Course Name |
Data Analytics for Business
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
EISL 518
|
Fall/Spring
|
3
|
0
|
3
|
5
|
Prerequisites |
None
|
|||||
Course Language |
Turkish
|
|||||
Course Type |
Elective
|
|||||
Course Level |
Second Cycle
|
|||||
Mode of Delivery | Online | |||||
Teaching Methods and Techniques of the Course | Group WorkProblem SolvingCase StudyLecture / Presentation | |||||
National Occupation Classification | - | |||||
Course Coordinator | ||||||
Course Lecturer(s) | ||||||
Assistant(s) | - |
Course Objectives | The course aims to show the usefulness of data-driven approach in business life. Its goal is to teach essential data science knowledge, tools, and practice in the analysis of business problems. |
Learning Outcomes |
The students who succeeded in this course;
|
Course Description | This course shows how to exploit data analytics in business problems. It teaches the application of data analytic techniques on business problems via an open source programming language. |
|
Core Courses | |
Major Area Courses |
X
|
|
Supportive Courses | ||
Media and Management Skills Courses | ||
Transferable Skill Courses |
Week | Subjects | Related Preparation | Learning Outcome |
1 | Introduction to Business Analytics and R | Chapters 2 & 3 (p. 30-80). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları. Nobel Akademik Yayıncılık. ISBN: 978-625-417-474-2 | |
2 | Creating Data Sets for Business Problems | Chapter 4 (p. 84-120). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları | |
3 | Making Data Ready for Business Analysis | Chapter 4 (p. 84-120). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları | |
4 | Making Data Ready for Business Analysis | Chapters 10 & 11 (p. 177-191). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu. Pusula. ISBN: 6056460894 | |
5 | Gaining Insights on Business Problems by Visualizing Data | Chapter 14 (p. 249-308). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu | |
6 | Gaining Insights on Business Problems by Visualizing Data | Chapter 14 (p. 249-308). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu | |
7 | Basic Statistics | ||
8 | Sales Data Analysis with Multiple Linear Regression | Chapter 16 (p. 339-357). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu | |
9 | Financial Risk Analysis with Multiple Logistic Linear Regression | Chapter 13 (p. 379-386). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları | |
10 | Product Defect Risk Analysis with Decision Trees | Chapter 11 (p. 284-313). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları | |
11 | Customer Segmentation | Chapter 8 (p. 208-232). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları | |
12 | Text Analysis on Customer Reviews | Chapter 17 (p. 460-491). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları | |
13 | Homework Presentations | ||
14 | Homework Presentations | ||
15 | Semester Review | ||
16 | Final Exam |
Course Notes/Textbooks | Hızıroğlu, A., Cebeci, H.İ., Codal K.Ç. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları. Nobel Akademik Yayıncılık. ISBN: 978-625-417-474-2
Arslan, İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu. Pusula. ISBN-10: 6056460894 |
Suggested Readings/Materials |
Semester Activities | Number | Weigthing |
Participation |
1
|
5
|
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments |
1
|
15
|
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
Midterm | ||
Final Exam |
1
|
80
|
Total |
Weighting of Semester Activities on the Final Grade |
2
|
20
|
Weighting of End-of-Semester Activities on the Final Grade |
1
|
80
|
Total |
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
3
|
48
|
Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
0
|
|
Study Hours Out of Class |
14
|
2
|
28
|
Field Work |
0
|
||
Quizzes / Studio Critiques |
0
|
||
Portfolio |
0
|
||
Homework / Assignments |
1
|
34
|
34
|
Presentation / Jury |
0
|
||
Project |
0
|
||
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
0
|
||
Final Exam |
1
|
40
|
40
|
Total |
150
|
#
|
PC Sub | Program Competencies/Outcomes |
* Contribution Level
|
||||
1
|
2
|
3
|
4
|
5
|
|||
1 |
To be able to demonstrate general business knowledge and skills. |
-
|
-
|
X
|
-
|
-
|
|
2 |
To be able to demonstrate business communication skills effectively. |
-
|
-
|
-
|
-
|
-
|
|
3 |
To be able to deliver creative and innovative solutions to the business-related problems. |
-
|
-
|
-
|
-
|
-
|
|
4 |
To be able to evaluate the performance of business organizations through a holistic approach. |
-
|
-
|
-
|
-
|
-
|
|
5 |
To be able to take a critical perspective in evaluating business knowledge. |
-
|
-
|
-
|
-
|
-
|
|
6 |
To be able to exhibit an ethical and socially responsible behavior in conducting research and making business decisions. |
-
|
-
|
-
|
-
|
-
|
|
7 |
To be able to solve business related problems using analytical and technological tools and techniques. |
-
|
-
|
-
|
-
|
X
|
|
8 |
To develop a solution to business problems through systematic research. |
-
|
-
|
X
|
-
|
-
|
|
9 |
To be able to use a foreign language to follow information about the field of business and participate in discussions in academic environments. |
-
|
-
|
-
|
-
|
-
|
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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