Data visualization is one of the top five skills required for data science (Harvard Business School). Aspiring data professionals, data analysts, and data scientists proficient in data visualization are in demand! This course gives you the data visualization skills and practical experience you need to catch an employer's eye in just 5 weeks.

During this course, also part of the IBM Data Analyst Professional Certificate, you’ll learn how to tell compelling stories through data visualization and transform raw data into meaningful insights. You’ll learn to use various Python tools and libraries, such as Matplotlib, Seaborn, Folium, Plotly, and Dash. You’ll also master how to analyze and present complex data in an accessible and engaging way, use basic and advanced plotting techniques, and create interactive dashboards.

As you work through the modules, you’ll explore:

Visualization tools such as:
Area plots
Histograms
Bar charts
Pie charts
Box plots
Scatter plots
Waffle charts
Word clouds
Geospatial maps.
How to build dashboards
How to create interactive data applications.

Additionally, you’ll gain valuable practical experience working on hands-on labs and a final project to analyze historical automobile sales data, visualize it, and then communicate your findings. Great experience to talk about in interviews!

If you want to build in-demand data visualization skills and enhance your data analytics job opportunities, enroll today. You have a great career ahead!

Course Syllabus

Module 1 -Introduction to Visualization Tools

Introduction to Data Visualization
Introduction to Matplotlib
Basic Plotting with Matplotlib
Dataset on Immigration to Canada
Line Plots

Module 2 -Basic Visualization Tools

Area Plots
Histograms
Bar Charts

Module 3 -Specialized Visualization Tools

Pie Charts
Box Plots
Scatter Plots
Bubble Plots

Module 4 -Advanced Visualization Tools

Waffle Charts
Word Clouds
Seaborn and Regression Plots

Module 5 -Creating Maps and Visualizing Geospatial Data

Introduction to Folium
Maps with Markers
Choropleth Maps

Learning Objectives

Implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium, to tell a stimulating story
Create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble
Create advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, and choropleth maps
Generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library

Recommended Skills Prior to Taking this Course

This is an intermediate-level course. We, therefore, recommend that you complete the Python for Data Analysis course and Data Science Project: Hands-on with Python Course before starting this one. All these courses are part of the IBM Data Analyst Professional Certificate.

Python for Data Visualization

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