Python for Data Analysts

Об этом курсе

The course includes a series of video lectures combined with a variety of conceptual and hands-on activities to help you develop the skills in Python to write commands, manipulate and analyse data, interpret results, and visualise data effectively.

The course begins with fundamental programming concepts, such as functions and statements. We then cover several of the Python libraries most relevant for data management and manipulation (i.e., NumPy, Pandas, Seaborn, and Matplotlib). You’ll also learn about extracting, transforming, and loading data (ETL) techniques and operations, as well as what is known as “data wrangling”.

The course is divided into four modules and includes knowledge tests at the end of each section.

Course Content

Module 1: Introduction to Programming with Python

Getting Started with Python; Performing Operations with Complex Data Types; Working with “If” Statements, Loops, and Comprehensions; Defining, Configuring, and Invoking Functions; Leveraging Functions with Lambdas, Generators, Closures, and Decorators

Module 2: Python for Data Science

Introduction to NumPy for Multi-dimensional Data; Advanced Operations with NumPy Arrays; Manipulating and Analysing Data in Pandas Dataframes; Data Wrangling with Pandas; Data Visualisation Using Seaborn

Module 3: Operations with petl

Petl: Introduction; Basic Data Transformations; Advanced Extractions and Transformations

Module 4: Data Science Statistics

Using Python to Compute and Visualise Statistics; Applied Inferential Statistics