Hands-on Data Science in R, New Zealand

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With the advent of big data, there is an increased focus on data mining and the value that can be derived from large data sets. Data mining is the process of selecting, exploring, and modeling large amounts of data to uncover previously unknown information for business benefit.

R is an open source software environment for statistical computing and graphics and is very popular with data scientists. R is being used for data analysis, extracting and transforming data, fitting models, drawing inferences, making predictions, plotting, and reporting results. Learn how to use R basics, working with data frames, data reshaping, basic statistics, graphing, linear models, non-linear models, clustering, and model diagnostics.

Attendees should have some coding experience, basic statistics.

Anyone interested in learning to use data mining techniques to find insights in data and who has at least some statistical and programming experience.

How to configure the RStudio environment and load R packages
How to use R basics such as basic math, data types, vectors, and calling functions
How to use advanced data structures such as data frames, lists, and matrices
How to use R base graphics
How to use R basic statistics, correlation, and covariance
How to use linear models such as simple linear regression, logistic regression
How to use non-linear models such as decision trees and Random Forests
How to apply clustering using K-means
How to complete model diagnostics

Course Objectives

How to configure the RStudio environment and load packages
How to use R basics such as basic math, data types, vectors, and calling functions
How to use advanced data structures such as data frames, lists, and matrices
How to use R base graphic packages
How to do exploratory data analysis
How to use R to support basic statistics, correlation, and covariance
How to use linear models such as linear regression and logistic regression
How to use models such as decision trees, Random Forest, and K nearest neighbor
How to use clustering models such as K-means

Course Structure

Modules:

Introduction to RStudio
R Basics
Introduction to Data Mining in R
Classification and Clustering Models in R
Summary

Module 1 Overview

Topics:

What is R?
What is RStudio?
Why use RStudio?
Navigating RStudio
What are packages?
How to install packages
Hands-on Exercises

Module 2 Overview

Topics:

R Math
Data Types
Working with Data
Loading Data
Writing Data
Data Structures
Hands-on Exercises

Module 3 Overview

Topics:

Overview of Data Mining and Data Science
Exploratory Data Analysis
Base Graphics in R
Linear Regression
Logistic Regression
Hands-on Exercises

Module 4 Overview

Topics:

Decision Trees
Clustering
Model Diagnostics
Hands-on Exercises

Module 5 – Summary

Skills Review

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

Upcoming Trainings

Join our public courses in our New Zealand facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

14 January 2025