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R for Data Science

Get hands-on experience of R for Data Science with the comprehensive course and lab. The lab provides hands-on learning of R programming language with a firm grip on some advanced data analysis techniques. The course and lab deal with the evaluation of data by using available R functions and packages. The course will help you to discover different patterns in datasets with the use of the R language, like cluster analysis, anomaly detection, and association rules. You will also learn to produce data and visual analytics through customizable scripts and commands.
  • Price: $279.99
  • Delivery Method: eLearning
NameBuy
R for Data Science
Test Prep
45+ Pre Assessment Questions | 45+ Post Assessment Questions |
Features
38+ LiveLab | 37+ Video tutorials | 01:59+ Hours
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  • Get assistance every step of the way from our Texas-based team, ensuring your training experience is hassle-free and aligned with your goals.
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  • Benefit from being taught by Professionally Certified Instructors with expertise in their fields and a strong commitment to making sure you learn and succeed.

Outline

Lessons 1:
Preface

  • What this course covers?
  • What you need for this course?
  • Who this course is for?
  • Conventions

Lessons 2:
Data Mining Patterns

  • Cluster analysis
  • Anomaly detection
  • Association rules
  • Questions
  • Summary

Lessons 3:
Data Mining Sequences

  • Patterns
  • Questions
  • Summary

Lessons 4:
Text Mining

  • Packages
  • Questions
  • Summary

Lessons 5:
Data Analysis – Regression Analysis

  • Packages
  • Questions
  • Summary

Lessons 6:
Data Analysis – Correlation

  • Packages
  • Questions
  • Summary

Lessons 7:
Data Analysis – Clustering

  • Packages
  • K-means clustering
  • Questions
  • Summary

Lessons 8:
Data Visualization – R Graphics

  • Packages
  • Questions
  • Summary

Lessons 9:
Data Visualization – Plotting

  • Packages
  • Scatter plots
  • Bar charts and plots
  • Questions
  • Summary

Lessons 10:
Data Visualization – 3D

  • Packages
  • Generating 3D graphics
  • Questions
  • Summary

Lessons 11:
Machine Learning in Action

  • Packages
  • Dataset
  • Questions
  • Summary

Lessons 12:
Predicting Events with Machine Learning

  • Automatic forecasting packages
  • Questions
  • Summary

Lessons 13:
Supervised and Unsupervised Learning

  • Packages
  • Questions
  • Summary