ECONOMICS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
ECO3564	Programming with Python	Spring	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	Turkish
Type of course:	Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Hybrid
Course Coordinator :	Dr. Öğr. Üyesi GÖKHAN ŞAHİN GÜNEŞ
Course Objectives:	The aim of this course is to introduce students how to search, visualize and analyse data needed to analyse economic, social and policy issues. By implementing a series of empirical projects based on publicly available data, students will be given the opportunity to gain hands-on experience with real-world data on issues of high importance to contemporary societies (inequality, social welfare, climate change, public health issues, etc.). Measuring the cost of unemployment, comparing banking systems or management practices around the world, etc. Important topics like this will be examined as a step-by-step research topic with the data that students can easily access and the programming language (Python) that can be used free of charge.

Learning Outcomes

The students who have succeeded in this course;
1. Software and statistical skills required by data collection, data processing, data cleaning processes
2. Learning how to collate various datasets and various programs
3. Research, practice and determine how to use the field analysis on theoretical and practical knowledge and skills gained in the field of economics, business and finance
4. Use of statistical tools in making forward-looking estimates
5. Able to obtain a good statistical knowledge of technical statistical analysis.

Course Content

Along with the basic programming concepts, the Python programming language to be used in the course will be introduced. Data cleaning, visualization and manipulation methods will be taught within the framework of introductory programming concepts. In this course, the basic philosophy of which is learning by doing, students will be encouraged to make empirical applications with real data in areas that are important for contemporary societies (e.g. inequality, welfare, public goods).

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Python	On software / handouts
2)	Collecting and analysing data from experiments	On software / handouts
3)	Application: Measuring climate change	On software / handouts
4)	Application: Measuring climate change	On software / handouts
5)	Application: Measuring the effect of a sugar tax	On software / handouts
6)	Application: Measuring the effect of a sugar tax	On software / handouts
7)	Application: Measuring wellbeing	On software / handouts
8)	Application: Measuring wellbeing	On software / handouts
9)	Application: Measuring inequality: Lorenz curves and Gini coefficients	On software / handouts
10)	Application: Measuring inequality: Lorenz curves and Gini coefficients	On software / handouts
11)	Application: Measuring management practices	On software / handouts
12)	Application: Measuring management practices	On software / handouts
13)	Application: Supply and demand	On software / handouts
14)	Application: Supply and demand	On software / handouts

Sources

Course Notes / Textbooks:	• "Doing Economics” by Eileen Tipoe and Ralf Becker. Link: https://www.core-econ.org/doing-economics/index.html • “Python Machine Learning”, by Wei-Meng Lee, John Wiley & Sons, Inc. (2019). • “R projects (for Dummies)”, by Joseph Schmuller, 2018, John Wiley & Sons, Inc., Hoboken, New Jersey.
References:

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	14	% 10
Project	6	% 50
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 10
PERCENTAGE OF FINAL WORK		% 90
Total		% 100

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	As a world citizen, she is aware of global economic, political, social and ecological developments and trends.	1
2)	He/she is equipped to closely follow the technological progress required by global and local dynamics and to continue learning.	4
3)	Absorbs basic economic principles and analysis methods and uses them to evaluate daily events.	4
4)	Uses quantitative and statistical tools to identify economic problems, analyze them, and share their findings with relevant stakeholders.	5
5)	Understands the decision-making stages of economic units under existing constraints and incentives, examines the interactions and possible future effects of these decisions.	4
6)	Comprehends new ways of doing business using digital technologies. and new market structures.	5
7)	Takes critical approach to economic and social problems and develops analytical solutions.	4
8)	Has the necessary mathematical equipment to produce analytical solutions and use quantitative research methods.	5
9)	In the works he/she contributes, observes individual and social welfare together and with an ethical perspective.	1
10)	Deals with economic problems with an interdisciplinary approach and seeks solutions by making use of different disciplines.	5
11)	Generates original and innovative ideas in the works she/he contributes as part of a team.	3