Learning R for Data Visualization

This course presents the theoretical and technical aspects necessary to master the art of scientific plotting in R in a colloquial manner. Unlike many other guides, this one is heavily practical, featuring bite-sized chunks of information as well detailed explanations and real results.

  • 2 hours 10 min of Self-paced Video
  • Learn how to visualize data and import/export in CSV, TXT, and Excel formats
  • See how to plot a distribution with histograms and box-plot
    Call Me

    Self-Paced

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    Course Features

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    About Learning R for Data Visualization

    The course is structured in simple lessons so that the learning process feels like a step-by-step guide to plotting. We start by importing data in R from popular formats such as CSV and Excel tables. Then you will learn how to create basic plots such as histograms, scatterplots, and more, with the default options, which guarantees stunning results.

    The second part of the course is dedicated to interactive plots. Static plots, in fact, are extremely important for scientific manuscripts, but nowadays most of our work is done online on websites and blogs, where static plots do not harness the full potential of the technology. Interactive plots, on the other hand, can improve that and allow us to present our results in more appealing and informative ways, by using the native language of the web. Do not worry though, you will not need to learn an additional programming language because this course will show you how to create stunning web plots directly from R.

    In the final part of the course, the Shiny package will be extensively discussed. This allows you to create fully-featured web pages directly from the R console, and Shiny also allows it to be uploaded to a live website where your peers and colleagues can browse it and you can share your work. You will see how to build a complete website to import and plot data, plus we will present a method to upload it for everybody to use. Finally, you will revise all the concepts you've learned while having some fun creating a complete website.

    By the end of the course, you will have an armour full of different visualization techniques, with the capacity to apply these abilities to real-world data sets.

    Course Objectives
    • See how to plot a distribution with histograms and box-plot
    • Deepen your knowledge by adding bar-charts, scatterplots, and time series plots using ggplot2
    • Enhance the user experience using dynamic visualisation
    • Save your work for publication, in tiff, at a good resolution
    • Test your coding limits by creating stunning interactive plots for the web
    • Create a fully-featured website using Shiny with real-time features such as adding and controlling functionalitiese
    Curriculum
    Module 1:

    Introducing Scientific Plotting In R

    • The Course Overview
    • Preview of R Plotting Functionalities
    • Introducing the Dataset
    • Loading Tables and CSV Files
    Module 2:

    Scientific Plotting In Ggplot2

    • Creating Histograms
    • The Importance of Box Plots
    • Plotting Bar Charts
    Module 3:

    Customizing Plots

    • Changing Theme
    • Changing Colors
    • Modifying Axis and Labels
    • Adding Supplementary Elements
    Module 4:

    Exporting Plots

    • Exporting Plots as Images
    • Adjusting the Page Size
    Module 5:

    Interactive Plots In Rcharts

    • Getting Started with Interactive Plotting
    • Creating Interactive Histograms and Box Plots
    • Plotting Interactive Bar Charts
    Module 6:

    Creating A Website With Shiny

    • Getting Started with Shiny
    • Creating a Simple Website
    • File Input
    • Conditional Panels – UI
    • Conditional Panels – Servers
    • Deploying the Site
    Instructor

    Self Paced courses are comprised of several learning videos into a course structure broken down into Learning Modules and Sessions. The learner is required to go through the videos topic-wise in the structure sequence of the course to learn the concepts. Being Self Paced, there is no intervention of any external faculty or additional mentor in learning.

    Certification

    NIIT Certification on completion of the program.

    Pre-requisites

    Basic knowledge of data analysitcs and basic programming background with Math or Science

    FAQs

    Who should go for this Course?

    IT Professionals looking forward to a career in Data Visualisation using Data Science concepts and working on Data interpretation and represntation using R Language.

    Where can I find my session schedule?

    The session schedule will be available in the training.com Student portal - Learning Plan section. You can login to your training.com account to view the same.

    What is your refund policy?

    Upon registering for the course, if for some reason you are unable or unwilling to participate in the course further, you can apply for a refund. You can initiate the refund any time before start of the second session of the course by sending an email to support@training.com , with your enrolment details and bank account details (where you want the amount to be transferred). Once you initiate a refund request, you will receive the amount within 21 days after confirmation and verification by our team. This is provided if you have not downloaded any courseware after registration.

    Why is it called Self Paced course?

    Self Paced courses are comprised of several learning videos into a course structure broken down into Learning Modules and Sessions. The learner is required to go through the videos topic-wise in the structure sequence of the course to learn the concepts. Being Self Paced, there is no intervention of any external faculty or additional mentor in learning.

    Being a self paced course, how will my attendance be tracked and marked?

    you login into your training.com account to watch the videos, attendance for it will be marked automatically.

    How will the assessment be conducted for my certification?

    After each module, a multiple choice questions type online assessment will be conducted. 5 Attempts will be allowed for the assessment to be completed. The minimum pass percentage for each assessment is 70%. On successfully clearing the assessment, a verified certificate from NIIT shall be awarded otherwise the certificate of participation will be issued.

    What are the minimum system requirements to attend the course?

      Minimum system requirements for accessing the courses are:

    • Personal computer or Laptop with web camera
    • Headphone with Mic
    • Minimum 4 Mbps broadband connection

    Is there an official support desk for technical guidance during the training program?

    Yes.For immediate technical support during the live online classroom sessions, you can call 91-9717992809 or 0124-4917203 between 9:00 AM and 8:00 PM IST. You can write to support@training.com for all other queries and our team will be happy to help you.

    Course Features

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