We are an inherently visual world, where images speak louder than words. Data visualization is

especially important when it comes to big data and data analysis projects. Nowadays more and

more companies are using machine learning to collect mass amounts of data. While it’s great that

they’re able to do this so quickly and effectively, it also calls for a way to sort through,

comprehend, and explain this data in a way that makes sense to both the business owners and

stakeholders. Python is a great language for doing data analysis, primarily because of the fantastic

ecosystem of data-centric Python packages. Pandas is one of those packages and makes

importing and analyzing data much easier. This course will take students from the basics of

Python to exploring many different types of data.

The course is divided into two sections. Section 1 includes an introduction to data visualization and section 2 includes python libraries used for data analysis and visualization.

Section 2 includes 8 lectures that explain various types of charts that are used in the decision-making process of an organization.

Businesses can now recognize patterns more quickly because they can interpret data in graphical or pictorial forms. Data visualization can benefit an organization in various ways to analyze:

• Correlations in Relationships

• Trends Over Time

• Examining the Market

• Risk and Reward

• Reacting to the Market