Programming and Data Management

Introduction

According to Statista, the annual amount of data created, captured, copied, and consumed worldwide will reach 97 zettabytes in 2022. Using available data to gain insights and make correct decisions is becoming essential for almost any business in today’s world.

This course introduces two of the most popular and indispensable programming languages for data analysts:

• Python (with focus on data cleaning, processing, analysis and visualization)
• SQL

In addition, the course also covers the basics of data management with focus on relational databases.

Course content

• Introduction, installation of Python, Jupyter lab, IDEs.
• Executing Python code.
• Variables, basic types, user input and output.
• Control flow (conditional execution, loops).
• Organizing code (functions and libraries).
• Data structures.
• Strings, reading, writing and processing text files. Regular expressions.
• Extracting data from web.
• Vectors and matrices (NumPy), random numbers and the Monte Carlo method.
• Processing and analyzing tabular data with Pandas (reading, cleaning, manipulating, grouping and aggregating data).
• Plotting and visualization (Matplotlib, Seaborn).
• Introduction to relational databases.
• Structured Query Language (SQL).
• The entity-relationship (ER) model and the relational model.
• Programming with databases.
• Indexes.
• Transactions.