Course Name Code Semester T+U Hours Credit ECTS
Data Analysis With Phyton ISE 448 8 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Prof.Dr. İSMAİL HAKKI CEDİMOĞLU
Course Lecturers
Course Assistants

 

 

 

 

Course Category Available Basic Education in the Field
Course Objective

Data Analysis with Python Programming Language, Basics of Python programming language is explained. The data analysis libraries of tPython programming language will be examined. Data analysis with Python programming language is carried out.

Course Content

Basic data types, Basic programming control structures, Data list creation and usage, tuples, Dictionaris, Arrays, Dataframe usage, 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, Drilland Practice, Motivations to Show, Testing,
4 Question-Answer, Discussion, Drilland Practice, Demonstration, Motivations to Show, Testing,
5 Question-Answer, Discussion, Drilland Practice, Demonstration, Motivations to Show, Testing,
Week Course Topics Preliminary Preparation
1 Introduction to Python Programming
2 Input, Processing and Output
3 Decision Structures
4 Looping Structures
5 Functions
6 File Handling
7 Lists and Tuples
8 Dictionaries
9 Series
10 DataFrames
11 Python Libraries for Data Analysis
12 Data Analysis Example
13 Data Analysis Example
14 Data Analysis Application
Resources
Course Notes <p>PPT Presentations, Python Program Codes.</p>
Course Resources

Python in 24 Hours, Sams Teach Yourself, Second Edition, Katie Cunningham, Sams Publihing, 2013. 

Machine Learning For Dummies, John Paul Mueller, Luca Massaron, John Wiley & Sons, 2016.

Pyhton for Data Analysis, Wes McKinney, O'Reilly Media, Inc., 2018.

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 X
2 X
3 X
4 X
5 X
6 X
7 X
8
9 X
10 X
11 X
12 X
Evaluation System
Semester Studies Contribution Rate
1. Ödev 100
Total 100
1. Yıl İçinin Başarıya 40
1. Final 60
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 7 7
Quiz 1 7 7
Assignment 1 9 9
Final examination 1 12 12
Total Workload 119
Total Workload / 25 (Hours) 4.76
dersAKTSKredisi 5