R for Data Science courses, July 2021.

All courses are live, online and instructor led.

Getting Started in R

A$990/attendee + gst

Learn how to import, visualise and analyse data in R, avoid common pitfalls and work with R objects/packages

Day/Time: 9 – 12pm, 12 & 13, July, 2021

Who will Benefit: Business analysts, Data scientists that are new-ish R users. No experience in R, is necessary. Course has largely been developed with input from customers, through experience in providing support, training and consulting.

  • Introduction to R
  • Accessing Help
  • Creating Working Directories for different projects.
  • R Language Objects & Classes
  • Data Import/Export
  • Data Manipulation including Stack, Subset & Merge
  • Data Analysis & Graphics 
    – Histograms, Box Plots, Bar Charts, Scatter Plots
    – Changing symbols, colours, style of points, axes, range etc
    – Labelling & Identifying Points. Adding Titles etc
    – Multiple Graphs on a single graphsheet.
    – Plotting Subsets of Rows
    – Adding points, lines, legends to existing plots
  • Exporting Graphics
  • Statistical Models in R 
    – Linear Regression
    – Non-linear Regression

Intermediate R

A$1,080/attendee + gst

Learn best practices, efficient code for data preparation, create advanced visualisations, run multiple regression models and tree based methods. 

Day/Time: 9 – 12pm, 19 & 20, July, 2021

Who will Benefit: Data scientists, quants + relatively new and existing R users.

Course outline:

  • Introduction & Preliminaries
  • Efficient use of R Language objects & functions
  • Programming in R – writing functions
  • Advanced Visualisations, including Trellis and ggplot2
  • Data Science/Predictive Modelling:
    – Multiple regression
    – Stepwise regression
    – Regression tree based methods
    – Accuracy measures
    – Validation
  • Unsupervised Learning methods
    – Heirarchical
    – Kmeans

Advanced R

A$1,080/attendee + gst

Analyse and visualise large datasets using the latest out-of-memory, big data packages. Build validated classification models, eg for Churn, cross/up-sell etc

Day/Time: 9 – 12pm, 26 & 27, July, 2021

Course outline:

  • Working with Big Data in R
    – Big data graphics, models and manipulation
  • Classification modelling:
    – Logistic regression 
    – Discriminant Analysis
    – Trees: Bagging, Random Forest & Boosting
    – SVM
    – Accuracy measures
    – Split/Cross Validation
  • Automation in R, including batch processing and deploying to production
  • Reporting: R Shiny and R Markdown

R Courses

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