R Language Training in Cambridge

R Markdown is an authoring framework that integrates executable R code with narrative text to produce dynamic and reproducible documents. This instructor-led, live training (online or onsite) is designed for beginner-level to intermediate-level R users who wish to generate automated, dynamic reports using R Markdown for government 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. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for government data analysts and individuals interested in learning how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis. By the end of this training, participants will be able to: - Conduct data analysis using Python, R, and SQL. - Generate insights through data visualization with Tableau. - Make data-driven decisions to enhance business operations for government.

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

Shiny is an R package that enables users to develop interactive and dynamic web applications directly from R, without the need for knowledge of JavaScript or complex web frameworks. This instructor-led, live training (online or onsite) is designed for intermediate-level R users who wish to build and deploy custom web applications using Shiny for data visualization, user interaction, and reporting in a government context. By the end of this training, participants will be able to: - Create interactive web applications using Shiny and R. - Design user interfaces with reactive elements and dynamic inputs. - Incorporate data visualizations and reporting features into Shiny apps. - Deploy and share Shiny apps locally or online via Shiny Server or Posit Cloud. **Format of the Course** - Interactive lecture and discussion. - Numerous exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options for Government** - To request a customized training for this course, tailored to specific government needs, please contact us to arrange.

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

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

• Effectively utilize Stata for data analysis and statistical modeling in public sector projects.
• Compare Stata’s functionalities with those of SPSS and R to make informed decisions for government workflows.
• Integrate Stata with R to enhance statistical computing capabilities for government initiatives.
• Develop and automate workflows using Stata and R to improve efficiency and accuracy in public sector tasks.

R is a widely used, open-source environment for statistical computing, data analytics, and graphical representation. This course introduces the R programming language to participants, covering language fundamentals, libraries, and advanced concepts. It includes advanced data analytics and graphing techniques using real-world data.

Audience

Developers and Data Analysts for government

Duration

3 days

Format

Lectures and Hands-on Exercises

Data analytics is a critical tool in the public sector today. This course will focus on developing practical, hands-on skills for government data analysis. The aim is to equip participants with the ability to provide evidence-based answers to key questions:

What has happened?

• processing and analyzing data
• creating informative data visualizations

What will happen?

• forecasting future performance for government operations
• evaluating the accuracy of forecasts

What should happen?

• transforming data into evidence-based decisions for government
• optimizing processes and workflows

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 contribute to this growing body of data.

This instructor-led, live course focuses on 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 their significance, enhancing decision-making processes for government.

Format of the Course

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

R is a widely used programming language in the financial sector. It is applied in various financial applications, from core trading systems to risk management frameworks.

In this instructor-led, live training, participants will learn how to leverage R to develop practical applications for addressing specific finance-related challenges.

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

• Comprehend the foundational principles of the R programming language
• Select and utilize R packages and techniques to organize, visualize, and analyze financial data from multiple sources (CSV, Excel, databases, web, etc.)
• Create applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Diagnose, integrate, deploy, and optimize an R application for government use

Audience

• Developers
• Analysts
• Quants

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• This training is designed to provide solutions for key challenges faced by finance professionals. If you have specific topics, tools, or techniques that you would like to add or delve deeper into, please contact us to arrange.

This instructor-led, live training in Cambridge (online or onsite) is designed for intermediate-level advanced R users who aim to enhance their skills in building faster workflows, improving code quality, and managing more complex analysis tasks for government.

By the end of this training, participants will be able to create reusable functions, optimize data workflows, debug and refine code, and generate reproducible reports.

This instructor-led, live training (online or onsite) is aimed at business analysts who wish to automate trade processes using algorithmic trading, Python, and R for government.

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

• Utilize algorithms to execute the buying and selling of securities at precise intervals rapidly.
• Minimize costs associated with trading through algorithmic methods.
• Automatically monitor stock prices and execute trades accordingly.

Big Data refers to technologies and solutions designed for storing and processing extensive data sets. Initially developed by Google, these Big Data solutions have since advanced and inspired numerous similar initiatives, many of which are now available as open-source projects. The programming language R is widely used in the financial sector and can also be leveraged for government applications to enhance data analysis and decision-making processes.

This instructor-led, live training in [location] (online or onsite) is designed for beginner-level data analysts who wish to utilize R programming to manage data, conduct basic data analysis, and produce insightful visualizations. By the end of this training, participants will be able to: - Grasp the fundamentals of R Programming. - Implement essential data science methodologies. - Generate visual representations of data to support decision-making for government.

This instructor-led, live training in [location] (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis for government. By the end of this training, participants will be able to: - Utilize cluster analysis for data mining. - Master R syntax for clustering solutions. - Implement both hierarchical and non-hierarchical clustering techniques. - Make data-driven decisions to enhance operational efficiency in public sector workflows.

This instructor-led, live training in Cambridge (online or onsite) is aimed at data scientists who wish to program in Python and R for KNIME for government applications.

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

• Plan, build, and deploy machine learning models in KNIME for government projects.
• Make data-driven decisions for operational improvements.
• Implement end-to-end data science projects within public sector workflows.

In this instructor-led, live training, participants will learn advanced techniques for Machine Learning with R as they develop 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 methods 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. - Deploy a model into production for use in a larger application. - Apply advanced machine learning techniques to address questions involving social network data, big data, and more, ensuring alignment with public sector workflows and governance for government.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by managers and data analysts in both the public and private sectors, including academia. R has also gained traction among statisticians, engineers, and scientists who may not have formal computer programming skills due to its user-friendly nature. The growing popularity of R can be attributed to its effectiveness in data mining for a range of objectives, such as optimizing advertising prices, accelerating drug discovery, and refining financial models. R offers a comprehensive array of packages that support robust data mining capabilities, making it a valuable tool for government and other organizations seeking to enhance their analytical processes.

Shiny is an open-source R package that offers a web framework for developing interactive web applications using R.

This instructor-led, live training is designed to equip participants with the skills needed to integrate data science and web development using Shiny, R, and HTML.

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

• Construct interactive web applications with R using Shiny

Audience

• Data scientists
• Web developers
• Statisticians

Format of the course

• The course combines lectures, discussions, and practical exercises with extensive hands-on practice to ensure a comprehensive learning experience.

This training is tailored to support public sector workflows, governance, and accountability for government professionals seeking to enhance their data visualization capabilities.

This instructor-led, live training (available online or on-site) is designed for government data analysts who wish to utilize Stata and R to conduct statistical analysis of big data. By the end of this training, participants will be able to: - Develop statistical models for predicting key variables and events. - Produce descriptive visualizations, summary tables, frequencies, and other relevant outputs. - Organize and manage large datasets to prepare for comprehensive data analysis for government purposes.

By the end of this training, participants will be able to: This instructor-led, live training (online or onsite) is designed for government data scientists who wish to program in R for Tableau. - Implement Tableau analytics using R. - Return values to Tableau by applying learning algorithms in R. - Structure and visualize R functions within Tableau. - Make data-driven decisions to enhance business operations for government.

Description:

This course is designed to equip R users with the skills needed to develop web applications without requiring a deep understanding of cross-browser HTML, JavaScript, and CSS.

Objective:

The course provides an overview of how Shiny apps function, ensuring participants understand the foundational concepts.

It covers all commonly used input, output, rendering, and paneling functions from the Shiny library, enabling users to create effective web applications for government use.

This instructor-led, live training in Cambridge (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 for government.

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.