how to take data that at first glance has little meaning and present that data in a form that makes sense to people.
how to use some data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium for presenting data.
“A picture is worth a thousand words”. We are all familiar with this expression. It especially applies when trying to explain the insights obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way.
In this course, you will learnhow to leverage a software tool to visualize datathat will also enable you to extract information, better understand the data, and make more effective decisions.
You can start creating your own data science projects and collaborating with other data scientists using IBM Watson Studio. When you sign up, you get free access to Watson Studio. Start now and take advantage of this platform.
Module 1 -Introduction to Visualization Tools
Introduction to Data Visualization
Introduction to Matplotlib
Basic Plotting with Matplotlib
Dataset on Immigration to Canada
Module 2 -Basic Visualization Tools
Module 3 -Specialized Visualization Tools
Module 4 -Advanced Visualization Tools
Seaborn and Regression Plots
Module 5 -Creating Maps and Visualizing Geospatial Data
Introduction to Folium
Maps with Markers
Python Basics for Data Science
Analyzing Data with Python