Offered By: IBM
Data Visualization with R
Data visualization is the presentation of data with graphics. It's a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this course you will learn how to create beautiful graphics and charts, customizing the look and feel of them as you wish.
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Data Visualization
7.17k+ EnrolledAt a Glance
Data visualization is the presentation of data with graphics. It's a way to summarize your findings and display it in a form that facilitates interpretation and can help in identifying patterns or trends. In this course you will learn how to create beautiful graphics and charts, customizing the look and feel of them as you wish.
ABOUT THIS COURSE
"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large data sets. 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. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions.
The main goal of this course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using the open source language R.COURSE SYLLABUS
Module 1 - Basic Visualization Tools
- Bar Charts
- Histograms
- Pie Charts
Module 2 - Basic Visualization Tools Continued
- Scatter Plots
- Line Plots and Regression
Module 3 - Specialized Visualization Tools
- Word Clouds
- Radar Charts
- Waffle Charts
- Box Plots
Module 4 - How to create Maps
- Creating Maps in R
Module 5 - How to build interactive web pages
- Introduction to Shiny
- Creating and Customizing Shiny Apps
- Additional Shiny Features
GENERAL INFORMATION
- This course is self-paced.
- It can be taken at any time.
- It can be audited as many times as you wish.
RECOMMENDED SKILLS PRIOR TO TAKING THIS COURSE
- Knowledge of R
REQUIREMENTS
- R101
COURSE STAFF
Saeed Aghabozorgi
Saeed Aghabozorgi, PhD is a Data Scientist in IBM with a track record of developing enterprise level applications that substantially increases clients’ ability to turn data into actionable knowledge. He is a researcher in data mining field and expert in developing advanced analytic methods like machine learning and statistical modelling on large datasets.
Polong Lin
Polong Lin is a Data Scientist at IBM in Canada. Under the Emerging Technologies division, Polong is responsible for educating the next generation of data scientists through BDU. Polong is a regular speaker in conferences and meetups, and holds a M.Sc. in Cognitive Psychology.
Course Development Team
Thanks to course developement team, interns and all individuals who contributed to the development of this course: João Henrique Rezende, Helly Patel , Mandeep Kaur , Hiten Patel , Marta Aghili , Anita Vincent , Iqbal Singh , Rishabh jain , Aditya Walia , Kumar Gaurav