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

This instructor-led, live training in Czech Republic (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 Czech Republic (online or onsite) is aimed at business analysts who wish to automate trading using 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 denotes the category of solutions designed for storing and processing extensive data sets. Initially developed by Google, these Big Data solutions have evolved and inspired numerous similar open-source projects. R is a widely used programming language within the financial sector.

This instructor-led, live training in Czech Republic (online or onsite) targets beginner-level data analysts who wish to utilize R programming for data manipulation, basic data analysis, and creating compelling visualizations to extract 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 Czech Republic (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 an essential asset. This course concentrates on building practical skills for hands-on data analysis. Our goal is to empower participants to provide evidence-based answers to key questions:

What has occurred?

• Processing and analyzing data
• Creating insightful data visualizations

What is projected to happen?

• Forecasting future performance
• Assessing the accuracy of forecasts

What should occur?

• Leveraging data to drive evidence-based business decisions
• Optimizing operational processes

This instructor-led, live training in Czech Republic (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 designed for statistical computing, data analytics, and data visualization. This course provides an introduction to the R programming language for students. It covers the fundamentals of the language, essential libraries, and advanced concepts, including practical applications of data analytics and graphing 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 Czech Republic (online or onsite) targets intermediate-level data analysts and business professionals aiming to conduct 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 in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Leverage the 'forecast' package to develop accurate forecasting models.
• Automate forecasting workflows for business and research applications.

This instructor-led, live training in Czech Republic (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.

It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.

This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.

By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.

Format of the Course

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

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

Upon completion, participants will be able to:

• Grasp and implement unsupervised learning methods
• Utilize clustering and classification to generate predictions from real-world data
• Visualize data to rapidly derive insights, facilitate decision-making, and refine analytical processes
• Enhance machine learning model performance via hyper-parameter tuning
• Deploy models into production environments for integration into larger applications
• Apply sophisticated machine learning techniques to address challenges involving social network data, big data, and other domains

R is a widely adopted programming language within the financial sector. It powers a diverse array of financial applications, spanning from core trading systems to sophisticated risk management solutions.

During this instructor-led live training, participants will acquire the skills necessary to leverage R for developing practical applications that address specific challenges in finance.

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

• Mastering the core principles of the R programming language
• Choosing and employing R packages and techniques to organize, visualize, and analyze financial data from multiple sources (such as CSV, Excel, databases, and web APIs)
• Constructing applications that resolve issues related to asset allocation, risk analysis, investment performance, and other areas
• Troubleshooting, integrating, deploying, and optimizing R applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• While this training focuses on providing solutions to key problems encountered by finance professionals, please contact us if you have a specific topic, tool, or technique you would like to include or explore in greater depth.

R is an open-source, freely available programming language designed for statistical computing, data analysis, and graphics. Its user base is expanding rapidly among managers and data analysts within both corporate and academic sectors. R has also attracted statisticians, engineers, and scientists who may lack extensive programming backgrounds but appreciate its accessibility. The language's popularity stems from the growing reliance on data mining for diverse objectives, such as setting optimal prices, accelerating drug discovery, or refining financial models. R supports this ecosystem with a comprehensive array of packages dedicated to data mining.

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.