Master 2021/2022

Data Analysis in Python

Category 'Best Course for Career Development'

Type: Elective course (Applied Economics and Mathematical Methods)

Area of studies: Economics

Delivered by: Department of Economics

Where: St.Petersburg School of Economics and Management

When: 2 year, 3 module

Mode of studies: distance learning

Online hours: 10

Open to: students of all HSE University campuses

Instructors: Andrei Ternikov

Master’s programme: Applied Economics and Mathematical Methods

Language: English

ECTS credits: 5

Contact hours: 4

Course Syllabus

Abstract

This course will introduce students to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library.

Learning Objectives

• introduce students to the basics of the python programming

Expected Learning Outcomes

• will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Course Contents

• Jupyter Notebook
• DataFrame structures
• Manipulating DataFrames
• Statistical techniques

Assessment Elements

• online
• exam
• online
• exam

Interim Assessment

• 2021/2022 3rd module
  0.5 * exam + 0.5 * online

Bibliography

Recommended Core Bibliography

• Nelli, F. (2015). Python Data Analytics : Data Analysis and Science Using Pandas, Matplotlib and the Python Programming Language. [Berkeley, CA]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1056488

Recommended Additional Bibliography

• CONTENTS 1 Blender/Python Documentation 3. (2011). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.3109D75A

Authors

• KRASILNIKOV ALEKSANDR ALEKSANDROVICH