Visualizing Data with Python

Course Description

"Visualizing Data with Python" is an intermediate-level course offered by IBM that focuses on the crucial skill of data visualization in the field of data science. This course is designed to equip learners with the tools and techniques necessary to create compelling visual representations of data using Python. By leveraging various data visualization libraries such as Matplotlib, Seaborn, and Folium, students will learn to transform complex datasets into clear, informative, and visually appealing graphics.

What students will learn

• Utilize Python's data visualization libraries to present data effectively
• Create and interpret basic visualization tools like area plots, histograms, and bar charts
• Develop specialized visualizations including pie charts, box plots, scatter plots, and bubble plots
• Implement advanced visualization techniques such as waffle charts, word clouds, and regression plots
• Visualize geospatial data and create interactive maps

Prerequisites

• Python Basics for Data Science
• Analyzing Data with Python
• Familiarity with basic Python programming concepts
• Understanding of fundamental data analysis principles

Course Content

• Introduction to data visualization and its importance in data science
• Basic plotting techniques using Matplotlib
• Area plots, histograms, and bar charts
• Specialized visualizations: pie charts, box plots, scatter plots, and bubble plots
• Advanced visualization tools: waffle charts, word clouds, and regression plots
• Geospatial data visualization using Folium
• Creating interactive maps with markers and choropleth maps
• Practical application of visualization techniques on real-world datasets

Who this course is for

This course is ideal for aspiring data scientists, data analysts, business intelligence professionals, and anyone looking to enhance their data visualization skills using Python. It's particularly suitable for individuals who have a basic understanding of Python programming and data analysis, and want to take their skills to the next level by learning how to create impactful visual representations of data.

Real-world Applications

• Create compelling presentations and reports for stakeholders
• Analyze and communicate trends in business metrics and KPIs
• Visualize scientific research findings
• Develop interactive dashboards for data exploration
• Enhance data journalism projects with informative graphics
• Improve user experience in data-driven applications and websites
• Support urban planning and development through geospatial visualizations

Syllabus