Data Analysis in Python

2021/2022

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered by:

Department of Applied Economics

Type:

Compulsory course

When:

1 year, 1-3 module

Instructor

Polyakov, Konstantin L.

Course Syllabus

Abstract

This course will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas and so on. The course is completely based on the specialization courses https://www.coursera.org/specializations/python#about: 1. Programming for Everybody (Getting Started with Python) https://www.coursera.org/learn/python?specialization=python 2. Data structures in Python https://www.coursera.org/learn/python-data?specialization=python 3. Using Python to Access Web Data https://www.coursera.org/learn/python-network-data?specialization=python 4. Using Databases with Python https://www.coursera.org/learn/python-databases?specialization=python 5. Capstone: Retrieving, Processing, and Visualizing Data with Python https://www.coursera.org/learn/python-data-visualization?specialization=python

Learning Objectives

• Learn how to get and analyze data using Python
• This course will take you from the basics of Python to exploring many different types of data.

Expected Learning Outcomes

• Accessing New Data Sources (Project)
• Basic Structured Query Language
• Building a Search Engine in Python
• Data Models and Relational SQL
• Databases and Visualization
• Definition of Functions in Python
• Exploring Data Sources (Project)
• Files processing in Python
• Installing and Using Python
• JSON and the REST Architecture
• Loops and Iteration in Python
• Many-to-Many Relationships in SQL
• Networks and Sockets in Python
• Object Oriented Programming in Python
• Programs that Surf the Web
• Regular Expressions in Python
• Spidering and Modeling Email Data
• Strings processing in Python
• The concept "Conditional Code"
• The concept of "dictionary" in Python
• The concept of "list" in Python
• The concept of "tuple" in Python
• Variables and Expressions
• Visualizing Email Data in Python
• Visualizing new Data Sources (Project)
• Web Services and XML in Python

Course Contents

• Programming for Everybody (Getting Started with Python)
• Data structures in Python
• Using Python to Access Web Data
• Using Databases with Python
• Retrieving, Processing, and Visualizing Data with Python

Assessment Elements

• The Final Exam
• Independent work
• Exploring Data Sources (Project)
  see https://www.coursera.org/learn/python-data-visualization?specialization=python
• Accessing New Data Sources (Project)
  see https://www.coursera.org/learn/python-data-visualization?specialization=python
• Visualizing new Data Sources (Project)
  see https://www.coursera.org/learn/python-data-visualization?specialization=python

Interim Assessment

• 2021/2022 3rd module
  0.6 * Independent work + 0.4 * The Final Exam

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

• Fabrizio Romano. (2018). Learn Python Programming : The No-nonsense, Beginner’s Guide to Programming, Data Science, and Web Development with Python 3.7, 2nd Edition: Vol. 2nd ed. Packt Publishing.

Authors

• POLYAKOV KONSTANTIN LVOVICH