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

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

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

• Use algorithms to rapidly buy and sell securities at specialized intervals.
• Reduce trade-related costs through algorithmic trading.
• Automatically monitor stock prices and execute trades.

Big Data refers to solutions designed for storing and processing large datasets. Originally developed by Google, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.

This instructor-led, live training in France (online or onsite) is designed for 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 in France (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.

In today's business landscape, data analytics serves as a vital asset. This course prioritizes the development of practical, hands-on skills for data analysis. The primary objective is to equip participants with the ability to provide evidence-based responses 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 France (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 used, open-source environment for statistical computing, data analytics, and graphics. This course introduces participants to the R programming language, covering language fundamentals, libraries, and advanced concepts, along with practical advanced data analytics and graphing using real-world data.

Audience

Developers / Data Analysts

Duration

3 days

Format

Lectures and Hands-on Practice

This instructor-led live training in France (online or onsite) is designed for intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

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

• Grasp the fundamentals of forecasting techniques within R.
• Apply ARIMA models and exponential smoothing methods for time series analysis.
• Utilize the 'forecast' package to develop accurate forecasting models.
• Automate forecasting workflows for both business and research purposes.

This instructor-led live training in France (online or onsite) is designed for data scientists who wish to program in Python and R for KNIME.

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

• Plan, build, and deploy machine learning models within KNIME.
• Make data-driven decisions for operations.
• Implement end-to-end data science projects.

In this instructor-led live training, participants will master advanced Machine Learning techniques using R by building a real-world application step-by-step.

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

• Comprehend and implement unsupervised learning methods
• Utilize clustering and classification to generate predictions from real-world datasets
• Visualize data to rapidly derive insights, support decision-making, and refine analytical processes
• Enhance machine learning model performance through hyper-parameter tuning
• Deploy models into production environments for integration into broader applications
• Apply sophisticated machine learning techniques to analyze social network data, big data, and other complex queries

R has established itself as a leading programming language within the financial sector. Its applications 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 applications that address specific finance-related challenges.

Upon completing this training, participants will be capable of:

• Grasping the fundamental concepts of the R programming language
• Choosing and employing R packages and methodologies to organize, visualize, and analyze financial data sourced from diverse channels (such as CSV, Excel, databases, and web APIs)
• Constructing applications that resolve issues related to asset allocation, risk analysis, investment performance, and more
• Effectively troubleshooting, integrating, deploying, and optimizing R applications

Audience

• Developers
• Analysts
• Quantitative Analysts (Quants)

Format of the course

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

Note

• While this training addresses key problems encountered by finance professionals, participants with specific topics, tools, or techniques they wish to explore in greater depth are encouraged to contact us for customization.

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 also allows for the evaluation of participants.

• 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, without needing any knowledge of JavaScript or complex web frameworks.

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

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

• Build interactive web applications using Shiny and R.
• Design user interfaces featuring reactive elements and dynamic inputs.
• Incorporate data visualization 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 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 it.

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

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

• Utilize Stata effectively 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.