Course Name Code Semester T+U Hours Credit ECTS
Data Analysis With Python ENF 548 0 3 + 0 3 6
Precondition Courses <p>Nothing</p>
Recommended Optional Courses <p>Nothing</p>
Course Language Turkish
Course Level yuksek_lisans
Course Type Optional
Course Coordinator Prof.Dr. İSMAİL HAKKI CEDİMOĞLU
Course Lecturers Prof.Dr. İSMAİL HAKKI CEDİMOĞLU,
Course Assistants
Course Category Available Basic Education in the Field
Course Objective

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.

Course Content

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.

# Course Learning Outcomes Teaching Methods Assessment Methods
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,
Week Course Topics Preliminary Preparation
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
Course Notes <p>PPT Slides,&nbsp;Python Program Codes.</p>
Course Resources

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.

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 X
2 X
3 X
4 X
5 X
7 X
8 X
9 X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 50
1. Ödev 50
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
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
Total Workload 140
Total Workload / 25 (Hours) 5.6
dersAKTSKredisi 6