| Ders Adı | Kodu | Yarıyıl | T+U Saat | Kredi | AKTS |
|---|---|---|---|---|---|
| Data Vısualızatıon | YBS 425 | 7 | 2 + 0 | 2 | 5 |
| Ön Koşul Dersleri | |
| Önerilen Seçmeli Dersler | |
| Dersin Dili | Türkçe |
| Dersin Seviyesi | Lisans |
| Dersin Türü | Seçmeli |
| Dersin Koordinatörü | Doç.Dr. HALİL İBRAHİM CEBECİ |
| Dersi Verenler | Doç.Dr. HALİL İBRAHİM CEBECİ, |
| Dersin Yardımcıları | |
| Dersin Kategorisi | Alanına Uygun Öğretim |
| Dersin Amacı | It is to provide students with the basic infrastructure on visualization of data analysis results and to create new designs with creative and critical thinking perspectives. |
| Dersin İçeriği | The course content includes business analytics applications and visualizations of these applications. |
| # | Ders Öğrenme Çıktıları | Öğretim Yöntemleri | Ölçme Yöntemleri |
|---|---|---|---|
| 1 | Can understand, organize and prepare any dataset for analysis | Lecture, Question-Answer, Drilland Practice, Problem Solving, Project Based Learning, | Homework, Project / Design, |
| 2 | Understands and implements data mining processes and interprets the results | Project Based Learning, Problem Solving, Lecture, | Project / Design, Homework, |
| 3 | Can do text preprocessing, analyze and interpret text. | Project Based Learning, Drilland Practice, Lecture, | Project / Design, Homework, |
| 4 | Processes, analyzes and interprets social media data. | Project Based Learning, | Project / Design, |
| 5 | Can make emotion inferences by processing texts and use these inferences for decision support. | Project Based Learning, Drilland Practice, | Performance Task, Project / Design, Homework, |
| 6 | Can use data visualization tools and prepare dynamic and integrated dashboards. | Project Based Learning, Drilland Practice, | Project / Design, Homework, |
| Hafta | Ders Konuları | Ön Hazırlık |
|---|---|---|
| 1 | Introduction to data visualization | |
| 2 | Data preprocessing and preparation processes (MS EXCEL and pivot table applications) | |
| 3 | Data preprocessing and preparation processes (MS EXCEL and pivot table applications) | |
| 4 | Data Mining applications (clustering and classification with Weka) | |
| 5 | Data Mining applications (Time Series Analysis with Weka) | |
| 6 | Text Mining Applications (TDM with R Software) | |
| 7 | Text Mining Applications (Visualization with Voyant) | |
| 8 | Text Mining Applications (Sentiment Analysis with Python) | |
| 9 | Midterm | |
| 10 | Social Media Analytics (Python) | |
| 11 | Data Visualization (Tableau) | |
| 12 | Data Visualization (Tableau) | |
| 13 | Data Visualization (Tableau) | |
| 14 | General assessment and Homework Presentations |
| Kaynaklar | |
|---|---|
| Ders Notu | Content shared from the system |
| Ders Kaynakları | Content shared from the system |
| Sıra | Program Çıktıları | Katkı Düzeyi | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Can follow new and current technologies and evaluate them | X | |||||
| 2 | Can understand the operation of Corporate Information Systems and use these systems at a basic level | X | |||||
| 3 | Constructs numerical models of basic business problems. | X | |||||
| 4 | Solves modeled business problems with the help of information technologies and interprets the solutions | X | |||||
| 5 | Contributes to informatics oriented projects as a member of the team | X | |||||
| 6 | Effectively uses information technology tools that support teamwork in project management. | X | |||||
| 7 | Master basic business functions and information technologies and establishes the link between them | X | |||||
| 8 | Contributes to the design, development and implementation processes of corporate information systems. | X | |||||
| 9 | Can produce and present quality documentation for all kinds of projects, including entrepreneurship projects. | X | |||||
| 10 | Prepares informative, effective and interesting presentations and presents these presentations. | ||||||
| Değerlendirme Sistemi | |
|---|---|
| Yarıyıl Çalışmaları | Katkı Oranı |
| 1. Ara Sınav | 40 |
| 1. Ödev | 20 |
| 2. Ödev | 25 |
| 3. Ödev | 15 |
| Toplam | 100 |
| 1. Yıl İçinin Başarıya | 60 |
| 1. Final | 40 |
| Toplam | 100 |
| AKTS - İş Yükü Etkinlik | Sayı | Süre (Saat) | Toplam İş Yükü (Saat) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 1 | 32 | 32 |
| Project / Design | 1 | 25 | 25 |
| Assignment | 2 | 10 | 20 |
| Mid-terms | 1 | 12 | 12 |
| Final examination | 1 | 25 | 25 |
| Toplam İş Yükü | 114 | ||
| Toplam İş Yükü / 25 (Saat) | 4,56 | ||
| Dersin AKTS Kredisi | 5 | ||