Mastering data visualisation opens the door to roles such as Data Analyst, Data Scientist, Business Intelligence Developer, and Visualization Engineer. These skills are highly sought after across industries including finance, healthcare, marketing, and tech, where visualising data to support decision-making is a top priority.
Course Features
Price
Original price was: £490.00.£14.99Current price is: £14.99.
Study Method
Online | Self-paced
Course Format
Reading Material - PDF, article
Duration
9 hours, 45 minutes
Qualification
No formal qualification
Certificate
At completion
Additional info
Coming soon
- Share
Overview
In the data-driven world we live in, the ability to visualise information clearly and effectively is a critical skill. This course takes a practical approach to mastering data visualisation in Python, guiding you from the fundamentals of Matplotlib to advanced interactivity with Plotly. You’ll start by building foundational skills in Matplotlib, learning to craft line plots, bar charts, histograms, subplots, and pie charts, all while working with real datasets like IMDB movie data.
As the course progresses, you’ll dive into Seaborn, a powerful statistical visualisation library built on top of Matplotlib. Here, you’ll explore complex visualisations like violin plots, boxen plots, pair plots, and regression plots that allow for deep insights into multi-dimensional datasets. You’ll also discover how to style and customise your visualisations to meet both aesthetic and analytical needs.
Further along, you’ll explore the plotting capabilities of Pandas, enabling quick and efficient plotting directly from DataFrames. From line and bar charts to hexbin and scatter matrices, you’ll learn how to use Pandas as a powerful tool for rapid visual exploration. Finally, the course unlocks the power of Plotly for building fully interactive charts, 3D plots, heatmaps, and bubble charts—ideal for dashboards and web applications.
By the end of this course, you’ll be equipped with the skills to choose the right type of visualisation for any dataset, enhance visual impact, and communicate complex insights effectively. Whether you’re analysing trends, exploring correlations, or presenting findings to stakeholders, this course ensures your data speaks with clarity and impact.
This course is perfect for data analysts, data scientists, business intelligence professionals, and students who want to master data visualisation in Python. It is also ideal for Python programmers who wish to communicate data insights more effectively through charts and visual storytelling.
Learners should have a basic understanding of Python programming and data analysis concepts. Familiarity with libraries like Pandas and NumPy is helpful but not mandatory, as key concepts are explained with practical demonstrations throughout the course.
Who is this course for?
In the data-driven world we live in, the ability to visualise information clearly and effectively is a critical skill. This course takes a practical approach to mastering data visualisation in Python, guiding you from the fundamentals of Matplotlib to advanced interactivity with Plotly. You’ll start by building foundational skills in Matplotlib, learning to craft line plots, bar charts, histograms, subplots, and pie charts, all while working with real datasets like IMDB movie data.
As the course progresses, you’ll dive into Seaborn, a powerful statistical visualisation library built on top of Matplotlib. Here, you’ll explore complex visualisations like violin plots, boxen plots, pair plots, and regression plots that allow for deep insights into multi-dimensional datasets. You’ll also discover how to style and customise your visualisations to meet both aesthetic and analytical needs.
Further along, you’ll explore the plotting capabilities of Pandas, enabling quick and efficient plotting directly from DataFrames. From line and bar charts to hexbin and scatter matrices, you’ll learn how to use Pandas as a powerful tool for rapid visual exploration. Finally, the course unlocks the power of Plotly for building fully interactive charts, 3D plots, heatmaps, and bubble charts—ideal for dashboards and web applications.
By the end of this course, you’ll be equipped with the skills to choose the right type of visualisation for any dataset, enhance visual impact, and communicate complex insights effectively. Whether you’re analysing trends, exploring correlations, or presenting findings to stakeholders, this course ensures your data speaks with clarity and impact.
This course is perfect for data analysts, data scientists, business intelligence professionals, and students who want to master data visualisation in Python. It is also ideal for Python programmers who wish to communicate data insights more effectively through charts and visual storytelling.
Learners should have a basic understanding of Python programming and data analysis concepts. Familiarity with libraries like Pandas and NumPy is helpful but not mandatory, as key concepts are explained with practical demonstrations throughout the course.
Mastering data visualisation opens the door to roles such as Data Analyst, Data Scientist, Business Intelligence Developer, and Visualization Engineer. These skills are highly sought after across industries including finance, healthcare, marketing, and tech, where visualising data to support decision-making is a top priority.
Requirements
In the data-driven world we live in, the ability to visualise information clearly and effectively is a critical skill. This course takes a practical approach to mastering data visualisation in Python, guiding you from the fundamentals of Matplotlib to advanced interactivity with Plotly. You’ll start by building foundational skills in Matplotlib, learning to craft line plots, bar charts, histograms, subplots, and pie charts, all while working with real datasets like IMDB movie data.
As the course progresses, you’ll dive into Seaborn, a powerful statistical visualisation library built on top of Matplotlib. Here, you’ll explore complex visualisations like violin plots, boxen plots, pair plots, and regression plots that allow for deep insights into multi-dimensional datasets. You’ll also discover how to style and customise your visualisations to meet both aesthetic and analytical needs.
Further along, you’ll explore the plotting capabilities of Pandas, enabling quick and efficient plotting directly from DataFrames. From line and bar charts to hexbin and scatter matrices, you’ll learn how to use Pandas as a powerful tool for rapid visual exploration. Finally, the course unlocks the power of Plotly for building fully interactive charts, 3D plots, heatmaps, and bubble charts—ideal for dashboards and web applications.
By the end of this course, you’ll be equipped with the skills to choose the right type of visualisation for any dataset, enhance visual impact, and communicate complex insights effectively. Whether you’re analysing trends, exploring correlations, or presenting findings to stakeholders, this course ensures your data speaks with clarity and impact.
This course is perfect for data analysts, data scientists, business intelligence professionals, and students who want to master data visualisation in Python. It is also ideal for Python programmers who wish to communicate data insights more effectively through charts and visual storytelling.
Learners should have a basic understanding of Python programming and data analysis concepts. Familiarity with libraries like Pandas and NumPy is helpful but not mandatory, as key concepts are explained with practical demonstrations throughout the course.
Mastering data visualisation opens the door to roles such as Data Analyst, Data Scientist, Business Intelligence Developer, and Visualization Engineer. These skills are highly sought after across industries including finance, healthcare, marketing, and tech, where visualising data to support decision-making is a top priority.
Career path
In the data-driven world we live in, the ability to visualise information clearly and effectively is a critical skill. This course takes a practical approach to mastering data visualisation in Python, guiding you from the fundamentals of Matplotlib to advanced interactivity with Plotly. You’ll start by building foundational skills in Matplotlib, learning to craft line plots, bar charts, histograms, subplots, and pie charts, all while working with real datasets like IMDB movie data.
As the course progresses, you’ll dive into Seaborn, a powerful statistical visualisation library built on top of Matplotlib. Here, you’ll explore complex visualisations like violin plots, boxen plots, pair plots, and regression plots that allow for deep insights into multi-dimensional datasets. You’ll also discover how to style and customise your visualisations to meet both aesthetic and analytical needs.
Further along, you’ll explore the plotting capabilities of Pandas, enabling quick and efficient plotting directly from DataFrames. From line and bar charts to hexbin and scatter matrices, you’ll learn how to use Pandas as a powerful tool for rapid visual exploration. Finally, the course unlocks the power of Plotly for building fully interactive charts, 3D plots, heatmaps, and bubble charts—ideal for dashboards and web applications.
By the end of this course, you’ll be equipped with the skills to choose the right type of visualisation for any dataset, enhance visual impact, and communicate complex insights effectively. Whether you’re analysing trends, exploring correlations, or presenting findings to stakeholders, this course ensures your data speaks with clarity and impact.
This course is perfect for data analysts, data scientists, business intelligence professionals, and students who want to master data visualisation in Python. It is also ideal for Python programmers who wish to communicate data insights more effectively through charts and visual storytelling.
Learners should have a basic understanding of Python programming and data analysis concepts. Familiarity with libraries like Pandas and NumPy is helpful but not mandatory, as key concepts are explained with practical demonstrations throughout the course.
Mastering data visualisation opens the door to roles such as Data Analyst, Data Scientist, Business Intelligence Developer, and Visualization Engineer. These skills are highly sought after across industries including finance, healthcare, marketing, and tech, where visualising data to support decision-making is a top priority.
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- Introduction to Matplotlib 00:10:00
- Creating Line Plots – Part 1 00:10:00
- IMDB Movie Revenue Plot – Part 1 00:10:00
- IMDB Movie Revenue Plot – Part 2 00:10:00
- Line Plot – Rank vs Runtime, Votes, and Metascore 00:10:00
- Line Styling and Adding Labels 00:10:00
- Scatter, Bar, and Histogram Plots – Part 1 00:10:00
- Scatter, Bar, and Histogram Plots – Part 2 00:10:00
- Subplots – Part 1 00:10:00
- Subplots – Part 2 00:10:00
- Creating Multiple Subplots 00:10:00
- Creating Zoomed Sub-Figures 00:10:00
- Axis Limits, Legends, Grids, and Ticks 00:10:00
- Pie Charts and Saving Figures 00:10:00
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- Introduction to Seaborn 00:10:00
- Creating Scatter Plots 00:10:00
- Using Hue, Style, and Size – Part 1 00:10:00
- Using Hue, Style, and Size – Part 2 00:10:00
- Creating Line Plots – Part 1 00:10:00
- Creating Line Plots – Part 2 00:10:00
- Creating Line Plots – Part 3 00:10:00
- Subplots in Seaborn 00:10:00
- Using sns.lineplot() and sns.scatterplot() 00:10:00
- Creating Categorical Plots (catplot) 00:10:00
- Drawing Box Plots 00:10:00
- Drawing Boxen Plots 00:10:00
- Creating Violin Plots 00:10:00
- Creating Bar Plots 00:10:00
- Point Plots for Comparison 00:10:00
- Joint Plots for Bivariate Analysis 00:10:00
- Pair Plots for Dataset Overview 00:10:00
- Regression Plots for Linear Relationships 00:10:00
- Styling Seaborn Charts and Aesthetics 00:10:00
- Introduction to the IRIS Dataset 00:10:00
- Loading the IRIS Dataset in Pandas 00:10:00
- Creating Line Plots 00:10:00
- Using Secondary Axes 00:10:00
- Creating Bar and Horizontal Bar Charts 00:10:00
- Stacked Bar Plotting 00:10:00
- Drawing Histograms with Pandas 00:10:00
- Creating Box Plots 00:10:00
- Area and Scatter Plotting 00:10:00
- Creating Hexbin Plots 00:10:00
- Creating Pie Charts 00:10:00
- Scatter Matrix and Subplot Layouts 00:10:00
- Exam of Data Visualisation in Python: From Matplotlib to Plotly 00:50:00
Is this certificate recognized?
Yes, our premium certificate and transcript are widely recognized and accepted by embassies worldwide, particularly by the UK embassy. This adds credibility to your qualification and enhances its value for professional and academic purposes.
I am a beginner. Is this course suitable for me?
Yes, this course is designed for learners of all levels, including beginners. The content is structured to provide step-by-step guidance, ensuring that even those with no prior experience can follow along and gain valuable knowledge.
I am a professional. Is this course suitable for me?
Yes, professionals will also benefit from this course. It covers advanced concepts, practical applications, and industry insights that can help enhance existing skills and knowledge. Whether you are looking to refine your expertise or expand your qualifications, this course provides valuable learning.
Does this course have an expiry date?
No, you have lifetime access to the course. Once enrolled, you can revisit the materials at any time as long as the course remains available. Additionally, we regularly update our content to ensure it stays relevant and up to date.
How do I claim my free certificate?
I trust you’re in good health. Your free certificate can be located in the Achievement section. The option to purchase a CPD certificate is available but entirely optional, and you may choose to skip it. Please be aware that it’s crucial to click the “Complete” button to ensure the certificate is generated, as this process is entirely automated.
Does this course have assessments and assignments?
Yes, the course includes both assessments and assignments. Your final marks will be determined by a combination of 20% from assignments and 80% from assessments. These evaluations are designed to test your understanding and ensure you have grasped the key concepts effectively.
Is this course accredited?
We are a recognized course provider with CPD, UKRLP, and AOHT membership. The logos of these accreditation bodies will be featured on your premium certificate and transcript, ensuring credibility and professional recognition.
Will I receive a certificate upon completion?
Yes, you will receive a free digital certificate automatically once you complete the course. If you would like a premium CPD-accredited certificate, either in digital or physical format, you can upgrade for a small fee.
Course Features
Price
Original price was: £490.00.£14.99Current price is: £14.99.
Study Method
Online | Self-paced
Course Format
Reading Material - PDF, article
Duration
9 hours, 45 minutes
Qualification
No formal qualification
Certificate
At completion
Additional info
Coming soon
- Share
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