Online R Language Training in South Korea

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

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

Upon completing this training, participants will be able to:

• Construct R Markdown documents with embedded R code chunks and formatted text.
• Generate outputs in various formats, including HTML, PDF, and Word.
• Employ parameterized reports and conditional logic to create dynamic content.
• Customize document appearance using themes, templates, and LaTeX for professional presentations.

Course Format

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

Course Customization Options

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

This instructor-led, live training in South Korea (online or onsite) is designed for data analysts and anyone interested in learning how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis.

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

• Conduct data analysis utilizing Python, R, and SQL.
• Derive actionable insights through data visualization with Tableau.
• Facilitate data-driven decision-making for business operations.

This instructor-led live training in South Korea (online or onsite) targets beginner-level professionals seeking to clean and analyze data, perform 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.

Shiny is an R package that empowers users to construct interactive and dynamic web applications directly within 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 aiming to create and deploy custom web applications using Shiny for data visualization, user interaction, and reporting.

Upon completing this training, participants will be equipped to:

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

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in South Korea (online or onsite) is designed for intermediate to advanced-level computer science professionals seeking to leverage Stata for statistical analysis and integrate it with R.

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

• Effectively utilize Stata for data analysis and statistical modeling.
• Compare the functionalities of Stata with those of SPSS and R.
• Integrate Stata with R to facilitate seamless statistical computing.
• Develop and automate workflows using both Stata and R.

R is a widely popular, open-source environment designed for statistical computing, data analytics, and graphics. This course introduces students to the R programming language, covering its fundamental concepts, essential libraries, and advanced topics. Participants will engage in advanced data analytics and visualization techniques using real-world datasets.

Audience

Developers and data analysts

Duration

3 days

Format

Lectures combined with hands-on practice

Data analytics has become an essential asset for modern businesses. This course emphasizes the development of practical, hands-on data analysis skills. The primary objective is to equip participants with the ability to provide evidence-based responses to key business inquiries:

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

Unstructured data is estimated to constitute over 90% of all data, with a significant portion appearing in textual formats. This volume continues to expand rapidly through blog posts, tweets, social media interactions, and other digital content.

This instructor-led, live course focuses on extracting meaningful insights from this data. By leveraging the R language alongside Natural Language Processing (NLP) libraries, we integrate principles and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically decipher the meaning within text. Data samples can be provided in various languages depending on 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 blend of lectures, discussions, and intensive hands-on practice, supplemented by occasional assessments to evaluate understanding.

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

In this instructor-led live training, participants will learn how to leverage R to develop practical solutions for various finance-specific challenges.

Upon completing this training, participants will be able to:

• Master the fundamentals of the R programming language
• Select and apply R packages and techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web APIs, etc.)
• Construct applications that address issues such as asset allocation, risk analysis, investment performance evaluation, and more
• Troubleshoot, integrate, deploy, and optimize R applications

Audience

• Developers
• Analysts
• Quants

Course Format

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

Note

• This training is designed to provide solutions for key challenges faced by finance professionals. If there is a specific topic, tool, or technique you wish to include or explore in greater depth, please contact us to make arrangements.

This instructor-led, live training in South Korea (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 South Korea (online or onsite) is designed for business analysts aiming to automate trading using algorithmic trading, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized increments.
• Decrease trading costs through the use of algorithmic trading.
• Automatically monitor stock prices and execute trades.

Big Data refers to technologies designed for storing and processing large-scale datasets. Originally developed by Google, these Big Data solutions have evolved and inspired numerous similar open-source projects. R is a widely used programming language in the financial sector.

This instructor-led, live training in South Korea (online or onsite) targets beginner-level data analysts who intend to use R programming to manipulate data, perform basic data analysis, and create compelling visualizations to gain insights.

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

• Understand the basics of R Programming.
• Apply fundamental data science processes.
• Create visual representations of data.

This instructor-led, live training in South Korea (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.

This instructor-led, live training in South Korea (online or onsite) is aimed at beginner-level professionals who wish to gain a mastery of the fundamentals of R and how to work with data.

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

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

This instructor-led, live training in South Korea (online or onsite) is aimed at data scientists who wish to program 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.

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.
• 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 an open-source, free programming language designed for statistical computing, data analysis, and graphical visualization. An increasing number of corporate managers and data analysts in both industry and academia are utilizing R. It has also gained popularity among statisticians, engineers, and scientists who may lack formal computer programming skills, largely due to its user-friendly nature. This growing adoption is driven by the expanding role of data mining in diverse objectives, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R supports a wide array of packages tailored for data mining.

R is an open-source, free programming language designed for statistical computing, data analysis, and graphical visualization. Its user base is expanding rapidly among managers and data analysts in both corporate and academic sectors. Additionally, R has gained popularity among statisticians, engineers, and scientists who may lack traditional computer programming expertise, owing to its user-friendly interface. This growth is driven by the increasing reliance on data mining for diverse objectives, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R offers a comprehensive ecosystem of packages tailored for data mining tasks.

Designed for data scientists and statisticians who already possess fundamental coding skills in R and C++, this course focuses on elevating their R programming capabilities to an advanced level.

The primary goal is to provide a hands-on, advanced R programming experience for participants eager to implement these techniques in their professional roles.

Industry-specific examples are integrated to ensure the training is directly relevant to the audience's field.

Shiny is an open-source R package that serves as a web framework for developing interactive web applications in R.

This instructor-led live training enables participants to merge data science and web development by leveraging Shiny, R, and HTML.

Upon completing this training, participants will be able to:

• Develop interactive web applications using R and Shiny

Target Audience

• Data scientists
• Web developers
• Statisticians

Course Format

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

This instructor-led, live training in (online or onsite) is aimed at data analysts who wish to use Stata and R to analyze big data for statistical analysis.

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

• Create statistic models for predicting key interest variables and events.
• Generate descriptive visualizations, summary tables, frequencies, and more.
• Manage and structure large databases to preapare for data analysis.

Upon completing this training, participants will gain the ability to:

This instructor-led live training in South Korea (available online or onsite) is targeted at data scientists who wish to program R for Tableau.

• Integrate R-based analytics into Tableau.
• Return values to Tableau using R's machine learning algorithms.
• Organize and visualize R functions using Tableau.
• Drive business operational decisions through data analysis.

Description:

This course is tailored to help R users build web applications without requiring prior knowledge of cross-browser HTML, JavaScript, or CSS.

Objective:

Introduces the fundamental concepts behind how Shiny applications function.

Explores the most frequently used input, output, rendering, and paneling functions within the Shiny library.

This instructor-led, live training in South Korea (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.

Audience

• managers
• developers
• scientists
• students

Format of the course

on-line instruction and discussion OR face-to-face workshops

R is an open-source, free programming language designed for statistical computing, data analysis, and graphics. Its user base is expanding among managers and data analysts in both corporate and academic settings. Additionally, R has gained popularity among statisticians, engineers, and scientists who lack computer programming expertise due to its user-friendly nature. This growing adoption is driven by the increasing reliance on data mining for objectives such as setting optimal prices, accelerating drug discovery, and refining financial models. R boasts a comprehensive suite of packages tailored for data mining tasks.

This course focuses on manipulating objects in R, including data ingestion, package management, function creation, and generating insightful visualizations. It also covers data analysis using standard statistical models. Participants will learn to utilize the R software (https://www.r-project.org) through both command-line interfaces and graphical user interfaces (GUIs).