Machine Learning & Visualisation for Data Mining with R Training Course

Unearth vital business information with Visualisation & Machine Learning

Tailor this course for your business

Code: R2

Duration

2 Days

Looking for a cost effective solution that adds business value?

Our Machine Learning and Visualisation for Data Mining with R training course, while something of a mouthful, is essentially about exploring and generating value from your data.

This course provides an overview of methods of data exploration and covers some of the more important techniques in data analysis, i.e. looking for patterns and meaning in your data.

R is a language designed expressly to provide a statistical programming environment that includes extensive graphical capabilities. It has rapidly become the de facto standard for analysts across many disciplines.

You will learn how to produce general summary statistics and how to explore your data visually using graphical methods. You’ll also learn how to rearrange your data using cross tabulation and contingency tables to help spot potential patterns. You will also learn some of the basics of machine learning by cluster analysis (unsupervised machine learning) and regression analysis (supervised machine learning).

In a nutshell Who should attend On site Course syllabus

By the end of this course, you will have learnt:

Summarising data numerically with R

Tabulating data with R

Visualisation - Graphical summary of data with R

Unsupervised Machine Learning with R

Supervised Machine Learning with R

Who should attend

Anyone who needs to analyse data will find this course useful. The methods demonstrated here are applicable to multiple disciplines.

Prerequisites

You need to know some basics of working with R but knowledge of statistics or analytics is not essential. You’ll need a laptop computer with R installed. No other software is needed although a spreadsheet program would be a useful asset.

On site

We are very happy to put together an on-site Data Mining with R Training workshop based on your specific requirements, and can take into account your existing programming experience level and types of statistical analysis project to which you will be applying R.

Course syllabus

Summarising data numerically

Getting averages and other summary statistics
R-commands - mean, median, summary, apply, tapply, aggregate
Gaining some initial insights into your data.
Averages and other summary statistics

Tabulating data

Frequency (contingency) tables. Cross-tabulation
R commands - table, ftable, xtabs, colMeans, prop.table, margin.table, addmargins
How to transform data using contingency tables and cross-tabulation

Graphical summary of data

Summary graphs. Exploratory graphs
R commands - stripchart, dotchart, plot
Visualizing data
Graphs to help summarize data
Graphs to help explore data and view potential patterns

Unsupervised machine learning

Dissimilarity, Hierarchical clustering, K-means, Partitioning around Medoids, Fuzzy analysis
R commands - dist, hclust, cutree
Looking for clusters in your data
Methods of cluster analysis include hierarchical clustering, partitioning methods and agglomerative nesting
R commands - kmeans, pam, diana, agnes, fanny

Supervised machine learning

Regression analysis, Linear models, Curvilinear models, Non-Gaussian models
R commands - lm, coef, resid, plot, abline
Exploring relationships between factors in your data
Regression analysis includes linear and curvilinear models as well as non-Gaussian regression
R commands - glm

" Course was very relevant, and all the basic topics were covered. Good pace. "

Data Science with Python Training Course
MFA, Data Analyst [Remote online course]
ActiveViam

" It was very good. In particular the separated chat rooms used for some of the exercises worked very well. "

Data Science with Python Training Course
JHO, Data Analyst [Remote online course]
ActiveViam

"Mixture of lecture and tutorial content. "Learn by doing""

Data Science with Python Training Course
JD, Data Scientist
Winton Capital

" The Jupyter notebooks were really handy, and I liked the group work using the breakout room feature of Zoom. Although the participants were from different backgrounds, Marco handled this very well by constantly checking if anyone has questions, adding explanations and making sure that the pace is right for the group. "

Data Science with Python Training Course
FSK, Data Analyst [Remote online course]
ActiveVIam

We would love to hear from you

Speak to us on 020 3137 3920 or get in touch below

We use cookies on our website to provide you with the best user experience. If you're happy with this please continue to use the site as normal.
For more information please see our Privacy Policy.

I understand