Data Visualization with Python
Unleash the power of data through visualization and discover the stories your data has to tell with our comprehensive course on Data Visualization with Python. Learn to create static and interactive visualizations using Python’s most popular libraries such as Matplotlib, Seaborn, Plotly, Plotnine, and Altair, and gain practical experience through hands-on projects.
DIFFICULTY
Beginner to Intermediate
COURSE TYPE
SCHEDULE
Self-paced
PRE-REQUISITES
Basic understanding of programming and fundamental data concepts
TAGS
Data Visualization, Python, Matplotlib, Seaborn, Plotly, Pandas, Plotnine, Altair, Google Colab
What you'll learn
Importance of
Data Visualization
Understand the critical role of data visualization in data science and other fields.
Python
Visualization Libraries
Get acquainted with Matplotlib, Seaborn, Plotly, Pandas Visualization, Plotnine, and Altair.
Setting up
Google Colab
Learn how to use Google Colab as an environment for data visualization.
Basic Plotting
Techniques
Create line charts, bar charts,
histograms, and scatter plots.
histograms, and scatter plots.
Advanced
Visualization Techniques
Explore advanced plotting techniques using Plotnine, Plotly, and Altair.
Interactive
Visualizations
Learn to create interactive plots that allow user engagement.
What you will build in this course
Basic Plots
Develop line charts, bar charts, histograms, and scatter plots using Matplotlib and Seaborn.
Advanced Visualizations
Create multi-layered and interactive plots with Plotnine, Plotly, and Altair.
Data Analysis Projects
Complete projects such as visualizing the Iris dataset, analyzing the Titanic dataset, and creating interactive plots with Plotly.
Course Outline
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Frequently Asked Questions
How does this course address the challenges of choosing the right type of plot for different data?
The course includes detailed lessons on the strengths and best use cases for various types of plots. You will learn how to choose the appropriate visualization technique based on the data and the insights you aim to convey, ensuring that your visualizations are both effective and meaningful.
What kind of real-world datasets will we work with in this course?
This course uses a variety of real-world datasets, including the Iris dataset for flower classification, the Titanic dataset for survival analysis, and a sample e-commerce dataset for sales and customer analysis.
Will I learn to create interactive visualizations?
Yes, the course includes modules on creating interactive visualizations. You will learn to build interactive plots that allow users to engage with the data dynamically.
Can I apply the skills learned in this course to other programming languages or visualization tools?
While the course focuses on Python, the principles and techniques of data visualization you learn are transferable to other programming languages and tools such as R, Tableau, and Power BI. You will gain a solid foundation that can be applied in various contexts.
What resources are provided to help me practice data visualization skills?
The course includes practical exercises, real-world projects, datasets, and access to a community of learners. You will have ample opportunities to practice and refine your data visualization skills through hands-on activities.
Data Visualization with Python Course Description PDF
Download a copy of this course's description PDF
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Hands-On Learning
Learn by doing! Our AI school equips you with practical, real-world skills to apply AI concepts effectively. Success is measured by your achievements and your ability to solve real-life challenges.
Engaging Learning Materials
Enjoy a variety of interactive content, including video lessons, coding walkthroughs, eBooks, audiobooks, explainer videos, animated videos, and SCORM materials. These high-quality resources are designed to make learning both engaging and efficient.
Your Success, Our Priority
Your success drives us. Our programs give you the tools and strategies to thrive in the fast-changing world of AI. Learn to create AI solutions that deliver real value.