Introductory R (Basic to Intermediate) Training Course

This instructor-led, live training in Malaysia (online or onsite) is aimed at intermediate-level advanced R users who wish to use R to build faster workflows, improve code quality, and handle more complex analysis tasks.

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

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

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

Big Data refers to frameworks designed for storing and processing large volumes of data. Initially developed by Google, these Big Data solutions have evolved and inspired numerous similar projects, many of which are now available as open-source software. R is a widely adopted programming language within the financial sector.

This instructor-led, live training in Malaysia (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis.

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

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

Data analytics plays an essential role in modern business operations. Throughout this course, we will concentrate on building practical, hands-on skills for effective data analysis. The primary objective is to empower participants to provide evidence-based answers to key questions:

What has happened?

• processing and analyzing data
• producing informative data visualizations

What will happen?

• forecasting future performance
• evaluating forecasts

What should happen?

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

This instructor-led live training in Malaysia (online or on-site) is designed for beginner-level professionals who wish to clean and analyze data, make statistical projections, and create insightful visualizations 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 organize datasets using Python and Power Query.
• Perform statistical analysis and projections with R.
• Create professional dashboards and reports with Power BI.
• Integrate and analyze data from multiple sources effectively.

R is a widely utilized, open-source environment designed for statistical computing, data analytics, and graphical representation. This course provides students with an introduction to the R programming language, encompassing its core fundamentals, library usage, and advanced concepts. Participants will explore advanced data analytics and graphing techniques utilizing real-world datasets.

Target Audience

Developers and data analysts

Duration

3 days

Format

Instructional lectures combined with practical, hands-on exercises

This instructor-led, live training in Malaysia (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.
• Utilize the ‘forecast’ package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

This instructor-led live training in Malaysia (online or onsite) is aimed at data scientists who wish to programme in Python and R for 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 for operations.
• Implement end-to-end data science projects.

Unstructured data is estimated to make up over 90 percent of all data generated, with a significant portion in text format. Content such as blog posts, tweets, social media interactions, and other digital publications continuously expand this vast pool of information.

This instructor-led, live course focuses on extracting valuable insights and meaning from this data. By leveraging the R programming language alongside Natural Language Processing (NLP) libraries, we integrate principles from computer science, artificial intelligence, and computational linguistics to algorithmically interpret the semantics of text data. Data samples provided during the training are available in various languages, tailored to specific customer needs.

Upon completion of this training, participants will be capable of preparing datasets of varying sizes from diverse sources and applying appropriate algorithms to analyze and report on their significance.

Course Format

• A combination of lectures, discussions, and extensive hands-on practice, with occasional assessments to evaluate understanding.

In this instructor-led, live training, participants will explore advanced techniques for Machine Learning using R, guided through the development of a real-world application.

Upon completion 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.
• Visualize 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 adopted programming language within the financial sector. Its applications span from core trading systems to sophisticated risk management solutions.

Through this instructor-led live training, participants will learn to leverage R to create practical applications that address specific challenges in finance.

Upon completion of this training, participants will be able to:

• Grasp the fundamental concepts of the R programming language
• Choose and apply R packages and techniques to organise, visualise, and analyse financial data from diverse sources (such as CSV, Excel, databases, and web platforms)
• Develop applications that resolve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimise R applications

Audience

• Developers
• Analysts
• Quantitative Analysts (Quants)

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• This training is designed to offer solutions for key problems encountered by finance professionals. If you have a specific topic, tool, or technique you wish to include or expand upon, please contact us to arrange accordingly.

R is an open-source, free programming language designed for statistical computing, data analysis, and data visualization. Its adoption is expanding among managers and data analysts within both corporate and academic sectors. R has also gained popularity among statisticians, engineers, and scientists who may lack extensive programming expertise but appreciate its user-friendly nature. This widespread appeal stems from the growing reliance on data mining for diverse objectives, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R offers a comprehensive suite of packages tailored for data mining tasks.

R Markdown is an authoring framework that seamlessly integrates executable R code with narrative text to produce dynamic and reproducible documents.

Designed for beginner to intermediate R users, this instructor-led live training (available online or onsite) empowers participants to generate automated, dynamic reports using R Markdown for internal documentation, research publications, or web publishing.

Upon completion of this training, participants will be able to:

• Construct R Markdown documents that embed R code chunks alongside formatted text.
• Generate outputs in various formats, including HTML, PDF, and Word.
• Employ parameterized reports and conditional logic to create dynamic content.
• Customize the visual appearance of documents using themes, templates, and LaTeX for a professional finish.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

• To arrange customized training for this course, please contact us.

Shiny is an R package that empowers users to create interactive and dynamic web applications directly from R, eliminating the need for JavaScript expertise or complex web frameworks.

This instructor-led live training, available online or on-site, is designed for intermediate-level R users who want to build and deploy custom web applications using Shiny for data visualization, user engagement, and reporting.

Upon completion of this training, participants will be able to:

• Develop interactive web applications using Shiny and R.
• Design user interfaces featuring reactive elements and dynamic inputs.
• Integrate data visualizations and reporting capabilities into Shiny apps.
• Deploy and share Shiny apps locally or online via Shiny Server or Posit Cloud.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live laboratory environment.

Customization Options

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