Introductory R (Basic to Intermediate) 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 (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 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.

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.

In this instructor-led, live training, participants will learn advanced techniques for Machine Learning with R as they step through the creation of a real-world application.

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

• Understand and implement unsupervised learning techniques
• Apply clustering and classification to make predictions based on real-world data.
• Visualise data to quickly gain insights, make decisions and further refine analysis.
• Improve the performance of a machine learning model using hyper-parameter tuning.
• Put a model into production for use in a larger application.
• Apply advanced machine learning techniques to answer questions involving social network data, big data, and more.

R is a widely used programming language within the financial sector. It powers a broad spectrum of financial applications, from core trading systems to risk management platforms.

In this instructor-led, live training, participants will learn how to harness R to build practical solutions for a range of specific finance-related challenges.

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

• Grasp the fundamentals of the R programming language
• Select and apply R packages and techniques to organise, visualise, and analyse financial data from diverse sources (CSV, Excel, databases, web, etc.)
• Develop applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimise an R application

Audience

• Developers
• Analysts
• Quants

Course Format

• A blend of lecture, discussion, exercises, and extensive hands-on practice

Note

• This training is designed to address some of the key challenges faced by finance professionals. However, if you have a specific topic, tool, or technique you would like to explore in greater depth or add to the curriculum, please contact us to arrange this.

R Markdown is an authoring framework that combines executable R code with narrative text to create dynamic and reproducible documents.

This instructor-led, live training (available online or on-site) is designed for beginner to intermediate R users who want to produce automated, dynamic reports using R Markdown for internal documentation, research publications, or web publishing.

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

• Create R Markdown documents with embedded R code chunks and formatted text.
• Generate outputs in multiple formats, including HTML, PDF, and Word.
• Use parameterised reports and conditional logic to generate dynamic content.
• Customise document appearance using themes, templates, and LaTeX for professional presentation.

Course Format

• Interactive lectures and discussions.
• Abundant exercises and hands-on practice.
• Real-time implementation in a live-lab environment.

Course Customisation Options

• To request a customised version of this course, please contact us to arrange.

Shiny is an R package that enables users to build interactive and dynamic web applications directly from R, without requiring knowledge of JavaScript or complex web frameworks.

This instructor-led, live training (online or onsite) is aimed at intermediate-level R users who wish to build and deploy custom web applications using Shiny for data visualisation, user interaction, and reporting.

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

• Create interactive web applications using Shiny and R.
• Design user interfaces with reactive elements and dynamic inputs.
• Incorporate data visualisations and reporting features into Shiny apps.
• Deploy and share Shiny apps locally or online via Shiny Server or Posit Cloud.

Format of the Course

• Interactive lecture and discussion.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Shiny is an open-source R package that provides a web framework for building interactive web applications using R.

In this instructor-led, live training, participants will learn how to combine data science and web development using Shiny, R, and HTML.

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

• Build interactive web applications with R using Shiny

Audience

• Data scientists
• Web developers
• Statisticians

Format of the course

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

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level to advanced-level computer science professionals who wish to leverage Stata for statistical analysis and integrate it with R.

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

• Effectively use Stata for data analysis and statistical modelling.
• Compare Stata’s functionalities with SPSS and R.
• Integrate Stata with R for seamless statistical computing.
• Develop and automate workflows using Stata and R.