Introduction to Python and Data Analysis

Build Python data analysis skills with confidence

This four-day instructor-led Python data science course helps you learn Python and data analysis through practical exercises and hands-on experience. You will develop skills to clean, analyse and visualise data, helping you apply Python confidently in your day-to-day work while enhancing your understanding of data science methods and practical coding for career development. 

Learning objectives

By the end of this course, you will be able to: 

  • Write Python scripts confidently 
  • Use Pandas for data handling 
  • Load and clean data for analysis 
  • Summarise and group data 
  • Create charts with Matplotlib 
  • Work in the JupyterLab environment 
  • Apply your learning directly to real data 

What you’ll learn

Learn to use Python for data analysis, from coding with variables, loops, and functions to working with Pandas and Matplotlib for data cleaning, analysis, and visualisation. This hands-on course builds your confidence using Python to manage and interpret data effectively in your work. 

Introduction to Python

Explore Python as an interpreted language, learning to work in script and interactive modes. You will cover writing statements, using comments effectively, and the importance of whitespace and indentation to write clear, readable code from the beginning – setting a strong foundation for more advanced programming tasks. 

Variables and scalar types

Learn about numerical, text and Boolean data types in Python and how to use variables as references within your scripts. You will also use the type() function to check and manage data types confidently during your coding exercises, helping you write more accurate and reliable code. 

Operators and expressions

Understand how to use arithmetic, assignment, comparison, logical and membership operators to perform calculations and comparisons within your Python scripts. These essential tools support accurate data handling and form the foundation for building effective, real-world analysis processes. 

Using containers in Python

Learn to use Python containers including lists, tuples, sets and dictionaries. These structures help you store, organise and access data efficiently, supporting robust analysis workflows in practical data projects and enabling you to manage complex data with ease. 

Writing functions

Understand how to define your own functions with positional and named arguments, including default values. You'll also learn to apply Python’s built-in functions like len(), sum(), min(), max() and sorted() to streamline your scripts and improve code reusability in real-world applications. 

What’s included
  • Four days of live instructor-led training 
  • Practical coding exercises 
  • Access to our live labs with real-time feedback 
  • Expert trainers with industry experience 
  • Course materials and data sets 
  • Certificate of completion 

Key facts

Ideal for

This Python data science course is ideal for professionals who want to learn Python for data analysis, including those who work with data in their roles and want to improve confidence and efficiency. 

Prerequisites

You should have experience with programming concepts such as variables, loops and functions, plus confidence with basic numeracy and interpreting charts to get the most from this course. 

Learning experience

Our experienced trainers and interactive labs create a focused, practical environment – so you can put theory into practice from day one. 

FAQs

StayAhead’s Introduction to Python and Data Analysis course introduces you to Python programming and its main data analysis tools, Pandas and Matplotlib, helping you learn to handle, analyse and visualise data confidently in your work. 

Do I need to prior knowledge of Python before attending this course?

No, but you should have experience with basic programming concepts including variables, loops, and functions. If you’re new to programming, we recommend completing our ‘Introduction to Programming – Python’ course first. If you have a numerate background and want to build practical data analysis skills using Python, this course will support you in confidently handling, exploring, and presenting data for your work. 

 

How is the course delivered?

Our Python data analysis course is delivered in live virtual classrooms by experienced instructors, using an interactive, hands-on approach. You’ll code alongside your trainer in a live lab environment, working through practical exercises that reflect real-world tasks. Upon completion, you’ll receive a StayAhead certificate, recognising the practical skills you’ve gained – ideal for supporting career development and enhancing your learning record.

How can Python skills benefit my career?

Python skills are highly valued across many industries, including data analysis, finance, and tech. Learning Python can help you automate tasks, analyse data effectively, and build tools that support business decision-making. It also demonstrates practical problem-solving skills, making you a more versatile and competitive candidate for a wide range of roles. 

How does the ‘Introduction to Python and Data Analysis’ course differ from the ‘Introduction to Python’ course?

The ‘Introduction to Python and Data Analysis’ course combines Python programming with practical data analysis using Pandas and Matplotlib, focusing on applying Python to clean, analyse, and visualise data in a business context. It is suited for those who already understand basic programming and want to use Python specifically for data tasks. 

In contrast, the ‘Introduction to Programming – Python' course is designed for complete beginners to programming. It introduces programming principles (such as variables, loops, and functions) using Python, along with Java and JavaScript examples, to build general coding confidence without focusing on data analysis. 

Why study with StayAhead
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30+ years’ experience

Industry-leading specialists delivering high-impact IT training  

Experiential instructor-led training

Courses are delivered by experienced instructors using hands-on, practical live labs 

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