Building Web Applications in R with Shiny 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.

Unstructured data is estimated to comprise over 90% of all existing data, with a significant portion existing as text. Sources such as blog posts, tweets, social media platforms, and other digital publications continuously contribute to this expanding volume of information.

This instructor-led, live course focuses on extracting meaningful insights from this 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 interpret the meaning behind textual data. Available data samples can be provided in various languages, tailored to specific customer requirements.

Upon completion of this training, participants will be equipped to prepare datasets of varying sizes from disparate sources and apply appropriate algorithms to analyze and report on their significance.

Format of the Course

• A blend of lectures, discussions, extensive hands-on practice, and occasional assessments to evaluate 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 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 is a free, open-source programming language designed for statistical computing, data analysis, and visualization. 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 lack extensive programming backgrounds, largely due to its user-friendly interface. The language's rise in prominence is driven by the growing demand for data mining across various domains, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R supports a vast ecosystem of packages tailored for data mining and analysis.

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.