Data Visualization for Data Science using R Data Visualization for Data Science using R

Data Visualization for Data Science using R

Data Visualization for Data Science using R

Course Provider

Data Visualization for Data Science using R

Course Highlights:

  • Data Visualization of Numeric data versus Non-numeric data
  • Design strategies for information Visualization such as Tuftes design principles
  • Representing and visualizing multiple variables. Chart selection such as Scatter plot, pie chart, histogram, boxplot, geospatial plots
  • Which graphs are most suitable?
  • Treating missing values, outliers
  • Get introduced to Spark concepts and set up the environment, A good understanding of RDD and working knowledge of RDD operations, Participants will have an overview of Spark architecture, concepts of performance tuning, Job submission, and job management.
  • FutureSkills Prime badge that can be added to your LinkedIn profile
  • Certificate by Jigsaw Manipal on course completion

What will you learn in Data Visualization for Data Science using R course?

In this course, you will learn-

  • The data storage type
  • Different types of data
  • Various analytical methods using a variety of tools
  • Data warehousing
  • Data manipulation
  • Hadoop for Big Data
  • HDFS
  • MapReduce program to process the data which gives a clear understanding of Big Data Engineering.

Data Visualization for Data Science using R

  • skill-type-icon Skill Type
    Emerging Tech
  • domain-icon Domain
    Big Data Analytics
  • course-category-icon Course Category
    Popular Tech Topics
    • cost-white-icon Course Price
      INR 6,999
      + 18% GST
    • duration-white-icon Course Duration
      36 Hours
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Why you should take Data Visualization for Data Science using R course?

  • Introduction to Big Data technologies
  • Challenges in the real-world data
  • How to store, analyze and get insight from the huge volume of data
  • How Hadoop distributed file storage works
  • Various components of Hadoop
  • MongoDB terminologies
  • Architecture
  • Key features and Indexing
  • Schema design
  • Challenges with RDBMS
  • Types of NoSQL database Get introduced to Spark concepts and set up the environment
  • A good understanding of RDD and working knowledge of RDD operations, participants will have an overview of Spark architecture
  • Concepts of performance tuning, Job submission, and job management

Who should take Data Visualization for Data Science using R course?

All IT people who want to switch to Data Engineering

Curriculum

  • Hadoop - History Architecture, Hadoop Components HDFS Architecture, HDFS Operations,
  • Hands-on Exercises on Jigsaw Lab
  • MapReduce Concept
  • MapReduce Architecture
  • YARN MapReduce Internals Hands-on Exercises
  • YARN MapReduce Internals Hands-on Exercises
  • Introduction to Spark and Set up, Spark Ecosystem and Abstractions, Programming in Scala, Sark Properties & Use Cases
  • Basics of RDD Operations, Transformations in RDD, Actions in RDD, Advanced RDD Operations RDD Persistence
  • Overview of Shared Variables - Accumulators, Job Submission & Execution, Performance Tuning, Job Scheduling and Management
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