What you’ll learn
Understand the core concepts of Data Visualization
Level-up Data Viz skills regardless of the programming language or visualization tool you use
What makes Data Visualization “Beautiful”?
Visualizing quantity of variables, their distributions and relationships
Appropriate charts and plots to use for appropriate data
Choosing colors, scales, fonts and symbols for elegant Data Visualization
Advanced Data Visualization with Python using Plotly, Seaborn and Matplotlib
This course will enhance a student’s understanding of charts, plots and graphs and bring it to a whole new level. Whether a student already knows something about Data Visualizations or not, they will definitely take something away after completing this course.
Although this course uses the Python Programming Language to create data visualizations, any other tool or programming language could be used to apply the principles that have been taught in this course.
– Achieve the main goal of data visualization which is to communicate data or information clearly and effectively to readers.
– Learn various do’s and don’ts of data visualizations, color scales and plot animation regardless of programming language or visualization tool.
– Visualize amounts, distributions, proportions, associations and time-series data.
– Learn how to visualize data like a pro.
– Make use of 3 different Python plotting libraries including Plotly, Seaborn, Matplotlib.
– Make use of your learnings to create beautiful data visualizations that could be used in print media, reports and social media.
– Master visual storytelling to communicate a message supported by the data.
– Identify trends and make data engaging and easily digestible
– Evoke an emotional response from whoever takes a look at your data visualized through various types of charts and plots.
Who this course is for:
- Data Science Enthusiasts
- Machine Learning Enthusiasts
- Graphic Designers
- Digital Marketers
Principles of Beautiful Data Visualization (2021)
Fundamental Principles, Cool Graphs & Charts in Python