Introductory R (Basic to Intermediate) Training Course

This instructor-led, live training in Slovakia (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 Slovakia (online or onsite) is designed for business analysts who wish to automate trading using algorithmic methods, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized increments.
• Lower costs associated with trading through the application of algorithmic methods.
• Automatically monitor stock prices and execute trades.

The term Big Data encompasses solutions designed for the storage and processing of massive datasets. Originally pioneered by Google, these Big Data solutions have evolved and inspired numerous similar projects, many of which are released as open-source software. R has established itself as a prominent programming language within the financial sector.

This instructor-led, live training in Slovakia (online or on-site) is targeted at data analysts who intend 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 a vital role in modern business. This course focuses on developing practical, hands-on data analysis skills. The primary goal is to equip participants with the ability 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 Slovakia (online or onsite) is designed for beginner-level professionals looking to clean and analyze data, generate statistical forecasts, and produce insightful visualizations using these tools.

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

• Grasp the fundamentals of using Python, R, Power Query, and Power BI for data analysis.
• Clean and organize datasets utilizing Python and Power Query.
• Conduct statistical analysis and forecasting with R.
• Develop professional dashboards and reports using Power BI.
• Effectively integrate and analyze data from diverse sources.

R is a widely adopted, open-source platform for statistical computing, data analytics, and graphics. This course provides students with an introduction to the R programming language, covering foundational language features, essential libraries, and advanced concepts. Participants will explore advanced data analytics and visualization techniques using real-world datasets.

Target Audience

Developers and data analytics professionals

Duration

3 days

Format

Lecture-based instruction combined with hands-on exercises

This instructor-led, live training in Slovakia (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 Slovakia (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.

Unstructured data is estimated to constitute over 90% of all data, with a significant portion appearing in textual form. Continuous contributions from blog posts, tweets, social media platforms, and other digital publications constantly expand this vast repository of information.

This instructor-led, live course focuses on extracting insights and meaning from such data. By leveraging the R language and Natural Language Processing (NLP) libraries, we integrate concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically decipher the meaning behind text data. Data samples can be provided in various languages, tailored to customer requirements.

Upon completion of this training, participants will be equipped to prepare datasets (both large and small) from diverse sources, then apply appropriate algorithms to analyze and report on their significance.

Course Format

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

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 has established itself as a leading programming language within the financial sector, powering applications that span from core trading systems to sophisticated risk management platforms.

Through this instructor-led live training, participants will gain the skills to leverage R for creating practical solutions to various finance-related challenges.

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

• Master the fundamental concepts of the R programming language
• Effectively select and apply R packages and methods to organize, visualize, and analyze financial data drawn from diverse sources such as CSV files, Excel spreadsheets, databases, and web APIs
• Develop applications that address key issues like asset allocation, risk analysis, and investment performance evaluation
• Debug, integrate, deploy, and optimize R-based applications

Audience

• Software Developers
• Financial Analysts
• Quantitative Analysts (Quants)

Course Format

• A balanced mix of lectures, interactive discussions, exercises, and intensive hands-on practice

Note

• While this training addresses major challenges encountered by finance professionals, specific topics, tools, or techniques you wish to explore in greater depth can be accommodated. Please contact us to arrange customized content.

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 within both corporate and academic sectors. R has also gained popularity among statisticians, engineers, and scientists who may lack formal computer programming training but find the platform intuitive and easy to use. Its widespread appeal stems from the growing demand for data mining techniques aimed at various objectives, such as optimizing pricing strategies, accelerating drug discovery, or refining financial models. R offers a comprehensive suite of packages tailored for data mining and analysis.

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

This instructor-led training session, available online or on-site, is designed for R users at beginner to intermediate levels who aim to generate automated, dynamic reports using R Markdown for purposes such as internal documentation, research publications, or web publishing.

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

• Create R Markdown documents that incorporate embedded R code chunks and formatted text.
• Produce outputs in various formats, including HTML, PDF, and Word.
• Utilize parameterized reports and conditional logic to generate dynamic content.
• Customize document appearance using themes, templates, and LaTeX for professional presentation.

Course Format

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

Course Customization Options

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

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

This instructor-led live training, available either online or on-site, targets intermediate R users who aim to develop and deploy custom web applications using Shiny for data visualization, user interaction, and reporting purposes.

Upon completion of this training, participants will be capable of:

• Developing interactive web applications utilizing Shiny and R.
• Constructing user interfaces featuring reactive elements and dynamic inputs.
• Integrating data visualizations and reporting capabilities into Shiny applications.
• Deploying and sharing Shiny applications locally or online via Shiny Server or Posit Cloud.

Course Format

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

Customization Options

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