If you are a beginner in R and want to get going with Machine Learning, then this course is for you. Based on a series of case studies, you will naturally and easily learn key skills in R. These skills will enable you to start to read, visualise and analyse data, and in addition they will give you the confidence and pre-requisites to progress to learning and carrying out Machine Learning analysis with the R language.
This course is often taken with our Machine Learning Concepts, Penalised Regression and Trees, Random Forests and Gradient Boosting Machines courses. Taken together, these courses will enable to you apply powerful Machine Learning techniques to the analysis tasks that you face and to communicate with Data Scientists using a shared vocabulary and methodology.
WHAT WILL I LEARN?
At the end of this course, you will be able to carry out initial end-to-end analyses of datasets, in R. In particular, you will be able to:
• Read data from different sources
• Carry out basic data cleansing and deal with missing values
• Manipulate data efficiently and quickly
• Perform insightful Exploratory Data Analysis, using graphs and maps where appropriate
• Carry out basic analyses using supervised and non supervised techniques
In addition, you will:
• Be aware of good programming practices in R and why you should keep to them
• Know which are the most popular and efficient R packages for various tasks
• Have a sufficient grounding in R to be able to take our more advanced courses on Machine Learning concepts and techniques.
WHO IS IT FOR?
No prior knowledge of R in necessary.