uCertify

R for Data Science

(DS-R.AJ1) / ISBN : 9781644593103

This course includes
Lessons
TestPrep
LiveLab

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.

Lessons

13+ Lessons | 110+ Exercises | 76+ Quizzes | 113+ Flashcards | 113+ Glossary of terms

TestPrep

45+ Pre Assessment Questions | 45+ Post Assessment Questions |

Hand on lab

38+ LiveLab | 37+ Video tutorials | 01:59+ Hours

Here's what you will learn

Download Course Outline

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

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

  • Patterns
  • Questions
  • Summary

  • Packages
  • Questions
  • Summary

  • Packages
  • Questions
  • Summary

  • Packages
  • Questions
  • Summary

  • Packages
  • K-means clustering
  • Questions
  • Summary

  • Packages
  • Questions
  • Summary

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

  • Packages
  • Generating 3D graphics
  • Questions
  • Summary

  • Packages
  • Dataset
  • Questions
  • Summary

  • Automatic forecasting packages
  • Questions
  • Summary

  • Packages
  • Questions
  • Summary

Hands-on LAB Activities

  • R Studio Sandbox

  • Plotting a Graph by Performing k-means Clustering
  • Calculating K-medoids Clustering
  • Displaying the Hierarchical Cluster
  • Plotting Graphs By Performing Expectation-Maximization
  • Plotting the Density Values
  • Computing the Outliers for a Set
  • Calculating Anomalies
  • Using the apriori Rules Library

  • Using eclat to Find Similarities in Adult Behavior
  • Finding Frequent Items in a Dataset
  • Evaluating Associations in a Shopping Basket
  • Determining and Visualizing Sequences
  • Computing LCP, LCS, and OMD

  • Manipulating Text
  • Analyzing the XML Text

  • Performing Simple Regression
  • Performing Multiple Regression
  • Performing Multivariate Regression Analysis

  • Performing Tetrachoric Correlation

  • Estimating the Number of Clusters Using Medoids
  • Performing Affinity Propagation Clustering

  • Grouping and Organizaing Bivariate Data
  • Plotting Points on a Map

  • Displaying a Histogram of Scatter Plots
  • Creating an Enhanced Scatter Plot
  • Constructing a Bar Plot
  • Producing a Word Cloud

  • Generating a 3D Graphic
  • Producing a 3D Scatterplot

  • Finding a Dataset
  • Making a Prediction

  • Using Holt Exponential Smoothing

  • Developing a Decision Tree
  • Producing a Regression Model
  • Understanding Instance-Based Learning
  • Performing Cluster Analysis
  • Constructing a Multitude of Decision Trees