Gain practical experience in data analysis and visualisation with Python, using powerful libraries like Pandas and Matplotlib. This course explores Python coding, DataFrames, functions, and visual data insights through hands-on exercises in JupyterLab, all within the Anaconda platform.
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Introduction to Python and Data Analysis
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Advance your Python data analysis abilities
Over four days of expert-led training, this Python course builds your data science capability through hands-on learning. You’ll gain the confidence to use Python for cleaning, analysing and visualising data, while deepening your understanding of core data science techniques and practical coding skills for professional growth.
Learning objectives
By the end of this course, you will be able to:
- Confidently write Python scripts
- Handle data using Pandas
- Load and prepare data for analysis
- Group and summarise data effectively
- Visualise data using Matplotlib
- Use the JupyterLab environment
- Apply skills to practical data tasks
What you’ll learn
Discover how to apply Python for data analysis, including variables, loops and functions, along with tools including Pandas and Matplotlib for data preparation, insight generation and visualisation. This practical course strengthens your ability to handle and interpret data confidently in real-world scenarios.
Getting started with Python
Explore Python as an interpreted language, using both interactive and script-based approaches. You’ll practise writing basic statements, structuring code with proper indentation and comments, and developing clean, readable scripts that lay the groundwork for future coding success across a range of technical applications.
Working with DataFrames
Learn to work with Pandas DataFrames, including loading and writing data, exploring datasets, subsetting and applying conditions, adding or dropping columns, performing aggregations and handling missing values – equipping you with the skills to manage, clean and interpret data confidently across a variety of real-world scenarios.
Grouping and aggregating data
Understand the split-apply-combine approach in Pandas by learning to group data by one or more columns and apply single or multiple aggregation functions. This method enables you to analyse trends, summarise large datasets and extract meaningful insights efficiently across varied data contexts.
Plotting with Matplotlib
Develop your ability to create effective visualisations using Matplotlib, including bar charts, histograms and line plots. You’ll learn to present your data analysis findings clearly, visually and professionally – supporting better communication of insights in reports, dashboards and presentations.
What’s included
- Four days of interactive, instructor-led training
- Hands-on coding practice throughout the course
- Use of live lab environments with guided feedback
- Industry experts delivering real-world insights
- Comprehensive course content and example data sets
- Course completion certificate recognising achievement
Key facts
Ideal for
Ideal for professionals working with data who want to develop practical Python skills, improve efficiency and gain confidence in analysis through hands-on training.
Prerequisites
Basic knowledge of programming concepts such as variables, loops, and functions, alongside confidence in numeracy and reading charts, will help you gain 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
ILX’s Introduction to Python and Data Analysis course provides practical training in Python, Pandas, and Matplotlib, helping you gain the confidence to manage, analyse, and visualise data effectively in your role.
Is this course suitable for beginners?
This course is best suited to those with some basic programming knowledge, including familiarity with variables, loops and functions. If you're completely new to coding, we recommend starting with our ‘Introduction to Programming – Python’ course. For anyone with a numerate background looking to build hands-on data analysis skills, this course offers practical experience in handling, exploring and presenting data using Python.
What is the course format?
This Python data analysis course is taught in a live virtual classroom by expert instructors. You'll take part in guided, interactive sessions that include practical coding exercises within a live lab environment. These exercises are designed to mirror real-world scenarios. After completing the course, you’ll receive a certificate from StayAhead, highlighting the practical capabilities you've developed to support your professional growth.
Are Python and data analysis skills in demand?
Yes, Python is in high demand across a range of industries, including technology, finance, healthcare and data analysis. Its versatility makes it ideal for automating tasks, building applications and, crucially, working with data. Python’s role in data analysis is particularly valuable – it enables professionals to clean, explore and visualise data, uncover insights and support smarter, evidence-based decisions.
As businesses increasingly rely on data to drive performance, having Python and data analysis skills can significantly boost your employability, provide new career opportunities and add measurable value to your organisation.
Why should I choose the ‘Introduction to Python and Data Analysis’ course?
This course is the perfect choice if you're looking to apply Python in a practical, business-focused way. It teaches you how to work with data using key libraries such as Pandas and Matplotlib, enabling you to clean, analyse and visualise information effectively.
By turning raw data into clear, actionable insights, you'll be better equipped to support decision-making, streamline reporting processes and contribute to data-driven initiatives in your organisation. For businesses, having employees with these skills means more efficient workflows, greater confidence in data interpretation and improved outcomes across teams and projects.
What our customers say
“Stuart was very good in explaining, and very patient, finding alternative ways to explain concepts where understanding was not grasped on the first attempt. Would recommend to all colleagues with an interest in data analysis.”
Stuart, Introduction to Python and Data Analysis learner
“Thoroughly enjoyed the course, very informative and a good balance between instruction and practical work.”
Megan, ILX learner
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