| Ders Adı | Kodu | Yarıyıl | T+U Saat | Kredi | AKTS |
|---|---|---|---|---|---|
| Data Analysıs Wıth Python | ENF 548 | 0 | 3 + 0 | 3 | 6 |
| Ön Koşul Dersleri | Nothing |
| Önerilen Seçmeli Dersler | Nothing |
| Dersin Dili | Türkçe |
| Dersin Seviyesi | YUKSEK_LISANS |
| Dersin Türü | Seçmeli |
| Dersin Koordinatörü | Prof.Dr. İSMAİL HAKKI CEDİMOĞLU |
| Dersi Verenler | Prof.Dr. İSMAİL HAKKI CEDİMOĞLU, |
| Dersin Yardımcıları | |
| Dersin Kategorisi | Alanına Uygun Temel Öğretim |
| Dersin Amacı | Attendees will be taught Data Analysis by using Python Programming Language. Python Programming language basics are explained. The data analysis libraries of the Python programming language will be examined. Data analysis examples are carried out. |
| Dersin İçeriği | Basic Python and pandas data types, Basic programming control structures, Basic libraries for data analysis, Data Structures, Data list creation and usage, Multidimensional arrays, Data frame and series, Data analysis. |
| # | Ders Öğrenme Çıktıları | Öğretim Yöntemleri | Ölçme Yöntemleri |
|---|---|---|---|
| 1 | Apply decision and repetition structures in program design | Drilland Practice, Problem Solving, Project Based Learning, | Project / Design, |
| 2 | Implement functions to improve efficiency of programs | Lecture, Question-Answer, Discussion, Drilland Practice, | Project / Design, |
| 3 | Write Python program codes to analyse datasets | Lecture, Question-Answer, Discussion, Demonstration, Motivations to Show, | Testing, |
| 4 | Data analysis with pandas library | Question-Answer, Discussion, Drilland Practice, Demonstration, Motivations to Show, | Testing, |
| 5 | Data analysis with pandas-profiling library | Question-Answer, Discussion, Drilland Practice, Demonstration, Motivations to Show, | Testing, |
| Hafta | Ders Konuları | Ön Hazırlık |
|---|---|---|
| 1 | Introduction to Python Programming Language | |
| 2 | Input, Processing, and Output | |
| 3 | Decision Structures | |
| 4 | Looping Structures | |
| 5 | Functions | |
| 6 | Lists and Tuples | |
| 7 | Dictionaries | |
| 8 | Series and Dataframes | |
| 9 | Data analysis with pandas library | |
| 10 | Data analysis with pandas-profiling library | |
| 11 | Python Libraries for Data Analysis | |
| 12 | Data Analysis Example | |
| 13 | Data analysis Example | |
| 14 | Data Visualization |
| Kaynaklar | |
|---|---|
| Ders Notu | PPT Slides, Python Program Codes. |
| Ders Kaynakları | Python in 24 Hours, Sams Teach Yourself, Second Edition, Katie Cunningham, Sams Publishing, 2013. Machine Learning For Dummies, John Paul Mueller, Luca Massaron, John Wiley & Sons, 2016. Python for Data Analysis, Wes McKinney, O'Reilly Media, Inc., 2018. The the Python Workshop: A Practical, No-Nonsense Introduction to Python Development, Andrew Bird, Dr Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade, Packt Publishing, 2019. |
| Sıra | Program Çıktıları | Katkı Düzeyi | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | X | ||||||
| 2 | X | ||||||
| 3 | X | ||||||
| 4 | X | ||||||
| 5 | X | ||||||
| 6 | |||||||
| 7 | X | ||||||
| 8 | X | ||||||
| 9 | X | ||||||
| Değerlendirme Sistemi | |
|---|---|
| Yarıyıl Çalışmaları | Katkı Oranı |
| 1. Ara Sınav | 50 |
| 1. Ödev | 50 |
| Toplam | 100 |
| 1. Yıl İçinin Başarıya | 50 |
| 1. Final | 50 |
| Toplam | 100 |
| AKTS - İş Yükü Etkinlik | Sayı | Süre (Saat) | Toplam İş Yükü (Saat) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 16 | 3 | 48 |
| Hours for off-the-classroom study (Pre-study, practice) | 12 | 3 | 36 |
| Mid-terms | 1 | 8 | 8 |
| Assignment | 1 | 24 | 24 |
| Final examination | 1 | 24 | 24 |
| Toplam İş Yükü | 140 | ||
| Toplam İş Yükü / 25 (Saat) | 5,6 | ||
| Dersin AKTS Kredisi | 6 | ||