Data Visualization with Python
Offered By: IBM via Coursera
Course Description
Overview
Visualizing data is used by virtually every discipline these days. It is used for analyzing web traffic to determine peak server load, growth and death rate of populations for biological analysis, analyzing weather patterns over time, stock market trends, and so on. Simply put, Data Visualization brings meaning to numbers that help people understand it. Seeing the data change can draw attention to trends and spikes that may otherwise go unnoticed. Python is an open-source (free) programming language has libraries that can be used to read and make useful graphics to present the data.
In this course, you will create an application that reads data from CSV files. You will learn how to visualize the data using various techniques using existing Python libraries.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Syllabus
- Data Visualization with Python
- Visualizing data is used by virtually every discipline these days. It is used for analyzing web traffic to determine peak server load, growth and death rate of populations for biological analysis, analyzing weather patterns over time, stock market trends, and so on. Simply put, Data Visualization brings meaning to numbers that help people understand it. Seeing the data change can draw attention to trends and spikes that may otherwise go unnoticed. Python is an open-source (free) programming language has libraries that can be used to read and make useful graphics to present the data. In this course, you will create an application that reads data from CSV files. You will learn how to visualize the data using various techniques using existing Python libraries.
Taught by
Alex Aklson
Tags
Related Courses
Social Network AnalysisUniversity of Michigan via Coursera Intro to Algorithms
Udacity Data Analysis
Johns Hopkins University via Coursera Computing for Data Analysis
Johns Hopkins University via Coursera Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX