Machine Learning in R - Training Course - Singapore
How to start with machine learning using R
- cluster analysis and
- create regression and classification models with random forests in R.
You will also be introduced to R in Power BI and how we can incorporate these analyses into a Power BI workflow. Training will be delivered by our experienced data scientist, Tamara Shatar PhD. Find more course details below.
Machine Learning in R - Training Course - Singapore
Frequently Asked Questions
Meet your Trainer

Tamara Shatar holds a PhD in Agricultural Data Science. She has extensive experience, including many years working as a research scientist focused on data analysis, modelling using machine learning, simulation and other techniques. While working in both academia and at the Australian CSIRO, part of her role included teaching a variety of data analysis skills. Tamara has designed our first Data Analytics Training Course, Using R, to provide beginners with the fundamental tools necessary to start using R for data analysis. She is consistently well reviewed by her students.
What is R?
R is an open source and free programming language that was developed for statistical analysis and production of high-quality graphics. It has long been popular with statisticians and academics who make up part of the large active user community behind R. This community has contributed over 15,000 packages that extend the base functionality of R, making it easy to implement a vast range of techniques for data manipulation, analysis and visualization.
What is Machine Learning?
Machine learning refers to a group of analysis techniques used to extract knowledge from data. It involves using mathematical or statistical models to predict outcomes. The models use algorithms (step-by-step programming instructions) to "learn" from data.
What is Remote Training?
Remote training at Nexacu, means our team of experienced trainers will deliver your training live online. With remote learning students can access our usual classroom training courses via video conferencing, ask questions, participate in discussion and share their screen with the trainer if they need help at any point. Students have the same level of participation and access to the trainer as they would in classroom training sessions.
Machine Learning in R Singapore Course Details


Data Analytics Course Outlines
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R Basics
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R Beginner
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R Intermediate
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Machine Learning in R
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R Programming Certification
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Machine Learning in R Certification
Skills Test
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What do I need to know to attend?
- Attended our R programming Foundations and Beginner courses or have basic familiarity with R.
- You will not be expected to code unassisted but will achieve better learning outcomes if you have a fundamental understanding of R syntax.
- Basic familiarity with Power BI is desirable (data import and creating basic visuals)
- Basic understanding of statistics (mean, median, standard deviation, variance)
Machine Learning in R Singapore Learning Outcomes
You will develop an understanding of and be able to:
- Generate insights from your data using cluster analysis
- Create predictive models from your data using random forests
- Assess the predictive accuracy of your classification and regression models
- Leverage models to make predictions to guide decision-making
- Incorporate R scripts in your Power BI workflow
Machine Learning in R Singapore Course Content
- Introduction
- Introduction to machine learning
- Supervised vs unsupervised learning
- The machine learning process
- Cluster analysis
- Purpose of cluster analysis
- Real-world applications
- K-means
- How the algorithm works
- Data preparation
- How many clusters?
- Performing k-means clustering in R
- Customer segmentation with cluster analysis
- Random forests
- Basics of tree-based models
- Classification vs regression trees
- From trees to forests
- Ensemble learning: bagging to reduce overfitting and improve predictive accuracy
- Preparing data for analysis
- Splitting data into training and test sets
- Training the model
- Assessing model accuracy
- Classification vs regression metrics
- Optimising the model
- Using the model for prediction
- R Scripts in Power BI
- Setting up
- Running R Scripts in Power Query to create new data
- Creating R visuals in Power BI