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Data Visualization with R

Beginnercourse

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.

4.6 (416 Reviews)

Language

  • English

Topic

  • Data Visualization

Enrollment Count

  • 8.65K

Skills You Will Learn

  • Data Science, Data Visualization

Offered By

  • CognitiveClass

Estimated Effort

  • 6 hours

Platform

  • SkillsNetwork

Last Update

  • April 30, 2024
About This course

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

Dr. Saeed Aghabozorgi, Data Visualization with R Course Instructor

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, Data Visualization with R Course Instructor

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

Instructors

Dr. 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.

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Svitlana Kramar

Data Scientist

I’m a passionate data science educator whose goal is to learn by teaching innovative data science tools that can improve our day-to-day tasks and our quality of life. My interests are in Natural Language Processing: text classification, summarization, and generation. Research can take a long time because there are a lot of resources and new opinions posted every day. Having tools to summarize and extract the information can save a lot of time. I hope we can all learn, approve, and apply the data science tools to cut down on the repetitive and tedious tasks, to make more informed decisions in life, to differentiate fake from real, and to open communication spaces to language-diverse or hearing-impaired audiences. The applications are limitless! My personality: I am a foodie and I love cooking and learning different cuisines. I also love travelling and connecting with people by learning a little bit of their language, about their food and music. I hold Data Science and Analytics master’s degree, specializing in Machine Learning, from University of Calgary.

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Polong Lin

Developer Advocate for Google Cloud

Polong Lin currently is a developer advocate helping Data Scientists to get the most out of Google Cloud. Prior to his current role Polong was a Data Scientist with the IBM Skills Network where he was responsible for educating the next generation of data scientists through BDU. Polong is a regular speaker at conferences and meetups, and holds an M.Sc. in Cognitive Psychology.

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