Master
2024/2025
Introduction to Python
Type:
Compulsory course (Economics and Economic Policy)
Area of studies:
Economics
Delivered by:
Department of Applied Economics
Where:
Faculty of Economic Sciences
When:
1 year, 1 module
Mode of studies:
distance learning
Online hours:
40
Open to:
students of all HSE University campuses
Instructors:
Konstantin Lvovich Polyakov
Master’s programme:
Economics and Economic policy
Language:
English
ECTS credits:
3
Course Syllabus
Abstract
This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis.
Learning Objectives
- This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python.
Expected Learning Outcomes
- Installing and using Python
- Strings Processing in Python
- Variables and expressions
- Use Loop and Conditional Statements
- Definition of functions in Python
- Files Processing in Python
- The Concept of "dictionary" in Python
- The Concept of "list" in Python
- The Concept of "tuple" in Python
- Regular expressions in Python
- Classes and Objects in Python
Course Contents
- Intro-01. Python basics. Variables, expressions and statements.
- Intro-02. Python control structures.
- Intro-03. Functions.
- Intro-04. Files
- Intro-05. Data structures.
- Intro-06. Regular Expressions
- Intro-07. Object-Oriented Programming
Bibliography
Recommended Core Bibliography
- Severance, C. (2016). Python for Everybody : Exploring Data Using Python 3. Place of publication not identified: Severance, Charles. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsotl&AN=edsotl.OTLid0000336
Recommended Additional Bibliography
- Python for data analysis : data wrangling with pandas, numPy, and IPhython, Mckinney, W., 2017