Shiny, R and HTML: Merging Data Science and Web Development Training Course

This instructor-led, live training in Sweden (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 Sweden (online or on-site) is designed for business analysts who wish to automate trading using algorithmic strategies, 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 trade-related costs by leveraging algorithmic trading.
• Automatically track stock prices and execute trades.

Big Data encompasses solutions designed for storing and processing extensive datasets. Originally developed by Google, these Big Data technologies have evolved and inspired numerous other initiatives, many of which are open-source. R is a widely used programming language within the financial sector.

This instructor-led, live training in Sweden (online or onsite) is aimed at beginner-level data analysts who wish to use R programming to manipulate data, perform basic data analysis, and create compelling visualizations for 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 session Sweden (online or onsite) targets data analysts looking 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 pivotal role in modern business. This course emphasizes the development of practical, hands-on data analysis skills, enabling 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 Sweden (online or onsite) is aimed at 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 for statistical computing, data analytics, and graphics. This course provides an introduction to the R programming language for students. It encompasses language fundamentals, libraries, and advanced concepts, along with practical data analytics and graphing techniques using real-world data.

Target Audience

Developers and data analytics professionals

Duration

3 days

Format

Lectures and hands-on exercises

This instructor-led, live training in Sweden (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 live, instructor-led training in Sweden (available online or onsite) is tailored for data scientists who wish to utilize Python and R for KNIME programming.

By the conclusion 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 has established itself as a highly popular programming language within the financial sector, utilized in applications that span from core trading platforms to sophisticated risk management systems.

Through this instructor-led live training, participants will acquire the skills necessary to leverage R for developing practical solutions to a variety of specific financial challenges.

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

• Comprehend the foundational concepts of the R programming language
• Select and employ R packages and techniques to organize, visualize, and analyze financial data sourced from various channels (such as CSV files, Excel, databases, web APIs, etc.)
• Construct applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Debug, integrate, deploy, and optimize 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 some of the key challenges encountered by finance professionals. Should you wish to customize the session by adding or elaborating on a specific topic, tool, or technique, please contact us to make the necessary arrangements.

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 (online or onsite) is aimed at beginner-level to intermediate-level R users who wish to generate 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 parameterized reports and conditional logic to generate dynamic content.
• Customize document appearance with themes, templates, and LaTeX for professional presentation.

Format of the Course

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

Course Customization Options

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

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

This instructor-led live training (available online or onsite) targets intermediate R users who want to build and deploy custom web applications using Shiny for data visualization, user interaction, and reporting.

Upon completing this training, participants will be able to:

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

Course Format

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

Customization Options for the Course

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

This instructor-led, live training in Sweden (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 modeling.
• Compare Stata’s functionalities with SPSS and R.
• Integrate Stata with R for seamless statistical computing.
• Develop and automate workflows using Stata and R.