Building Web Applications in R with Shiny Training Course

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level advanced R users who wish to leverage R to build faster workflows, enhance code quality, and tackle more complex analytical tasks.

By the end of this training, participants will be able to: create reusable functions, improve data workflows, debug and optimise code, and produce reproducible reports.

This instructor-led, live training in New Zealand (online or onsite) is aimed at business analysts who wish to automate trading using algorithmic strategies, Python, and R.

By the end of this training, participants will be able to:

• Use algorithms to buy and sell securities rapidly in specialised increments.
• Reduce trading-related costs through the application of algorithmic trading.
• Automatically monitor stock prices and execute trades.

Big Data is a term referring to solutions designed for storing and processing large-scale datasets. Initially developed by Google, these Big Data solutions have evolved and inspired numerous similar projects, many of which are available as open-source. R is a widely used programming language within the financial industry.

This instructor-led, live training in New Zealand (delivered online or on-site) is designed for beginner-level data analysts who wish to use R to manipulate data, perform foundational data analysis, and create compelling visualisations to derive insights.

By the end of this training, participants will be able to:

• Understand the fundamentals of R programming.
• Apply core data science processes.
• Create visual representations of data.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphics. It is increasingly adopted by managers and data analysts across corporations and academia. R has also gained traction among statisticians, engineers, and scientists who may lack formal programming skills but find the language intuitive to use. Its growing popularity stems from the expanding use of data mining for diverse objectives, such as setting advertising prices, accelerating drug discovery, or refining financial models. R offers a wide range of packages tailored for data mining tasks.

This instructor-led, live training in New Zealand (available online or on-site) is designed for data analysts who wish to programme with R in SAS for cluster analysis.

By the end of this training, participants will be able to:

• Apply cluster analysis for data mining purposes.
• Master R syntax for developing clustering solutions.
• Implement both hierarchical and non-hierarchical clustering techniques.
• Make data-driven decisions to help improve business operations.

Data analytics is a vital tool in today's business landscape. Throughout this course, we focus on building practical, hands-on skills for data analysis. The goal is to empower participants to provide evidence-based answers to key questions: 

What has happened?

• processing and analysing data
• creating insightful data visualisations

What will happen?

• forecasting future performance
• evaluating forecasts

What should happen?

• turning data into evidence-based business decisions
• optimising processes

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner-level professionals who wish to clean and analyse data, make statistical projections, and create insightful visualisations using these tools.

By the end of this training, participants will be able to:

• Understand the basics of Python, R, Power Query, and Power BI for data analysis.
• Clean and organise datasets using Python and Power Query.
• Perform statistical analysis and projections with R.
• Create professional dashboards and reports with Power BI.
• Integrate and analyse data from multiple sources effectively.

R is a widely used, open-source environment for statistical computing, data analytics, and graphics. This course introduces students to the R programming language, covering language fundamentals, libraries, and advanced concepts. Participants will explore advanced data analytics and visualisation using real-world datasets.

Audience

Developers and data analytics professionals

Duration

3 days

Format

Lectures and hands-on sessions

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner-level professionals seeking to master the fundamentals of R and learn how to work effectively with data.

By the end of this training, participants will be able to:

• Understand the R programming environment and the RStudio interface.
• Import, manipulate, and explore datasets using R commands and packages.
• Perform basic statistical analysis and data summarisation.
• Generate visualisations using both base R and ggplot2.
• Manage workspaces, scripts, and packages efficiently.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

By the end of this training, participants will be able to:

• Understand the fundamentals of forecasting techniques in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Utilise the 'forecast' package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphics. It is increasingly adopted by managers and data analysts across both corporate and academic sectors. R offers a wide array of packages tailored for data mining tasks.

This instructor-led, live training in New Zealand (online or on-site) is designed for data scientists who wish to program in Python and R within KNIME.

By the end of this training, participants will be able to:

• Plan, build, and deploy machine learning models in KNIME.
• Make data-driven decisions to support operations.
• Implement end-to-end data science projects.

It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.

This instructor-led, live course centres on extracting insights and meaning from this data. Using the R language and Natural Language Processing (NLP) libraries, we blend concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically interpret the meaning behind text data. Data samples are available in various languages, depending on customer requirements.

By the end of this training, participants will be able to prepare data sets (both large and small) from disparate sources and apply the appropriate algorithms to analyse and report on their significance.

Course Format

• Part lecture, part discussion, with extensive hands-on practice and occasional tests to assess understanding

Audience

Course Format

By the end of this training, participants will be able to:

In this instructor-led, live training, participants will learn how to manipulate and visualise data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modelling, and visualising data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and data visualisation

• Part lecture, part discussion, exercises and heavy hands-on practice

• Perform data analysis and create appealing visualisations
• Draw useful conclusions from various datasets of sample data
• Filter, sort and summarise data to answer exploratory questions
• Turn processed data into informative line plots, bar plots, histograms
• Import and filter data from diverse data sources, including Excel, CSV, and SPSS files