Data Management and Python Programming

Introduction

According to Statista, the annual amount of data created, captured, copied, and consumed worldwide will reach 120 zettabytes in 2023. 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.
• 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).
• Relational model.
• Programming with databases.
• Indexes.
• Transactions.