Building Web Applications in R with Shiny Training Course

This instructor-led, live training in Portugal (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 Portugal (online or onsite) is aimed at business analysts who wish to automate trade with 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 refers to the range of solutions designed for storing and processing extensive data sets. Originally developed by Google, these Big Data solutions have advanced and inspired numerous similar initiatives, many of which are now available as open-source projects. R has become a widely adopted programming language within the financial sector.

This instructor-led, live training in Portugal (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.

R is a free, open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by corporate managers, data analysts, and researchers in academia. R has also gained popularity among statisticians, engineers, and scientists who may lack traditional programming expertise but appreciate its user-friendly interface. The language's widespread adoption stems from the growing reliance on data mining to achieve diverse objectives, such as optimizing pricing strategies, accelerating drug discovery, and refining financial models. R offers a comprehensive suite of packages tailored for data mining tasks.

This instructor-led live training in Portugal (online or onsite) is designed for data analysts wishing 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 improve business operations.

Data analytics serves as an essential instrument for modern business operations. This course concentrates on cultivating practical skills for hands-on data analysis, empowering participants to provide evidence-based responses to critical inquiries:

What has occurred?

• processing and analysing data
• generating insightful data visualisations

What is anticipated to happen?

• forecasting future performance
• evaluating forecast accuracy

What ought to happen?

• transforming data into evidence-driven business decisions
• optimising operational processes

This instructor-led, live training in Portugal (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 analysis, and data visualisation. This course provides students with an introduction to the R programming language, covering its core fundamentals, essential libraries, and advanced concepts. Participants will explore advanced data analytics and graphical techniques applied to real-world datasets.

Target Audience

Developers and data analysts

Duration

3 days

Delivery Format

Lecture-based instruction combined with practical, hands-on exercises

This instructor-led, live training in Portugal (online or onsite) is designed for beginner-level professionals seeking to master the fundamentals of R and data processing.

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

• Understand the R programming environment and RStudio interface.
• Import, manipulate, and explore datasets using R commands and packages.
• Perform basic statistical analysis and data summarization.
• Generate visualizations using both base R and ggplot2.
• Manage workspaces, scripts, and packages effectively.

This instructor-led, live training in Portugal (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.

R is a free, open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by managers and data analysts within both corporate environments and academic institutions. R offers a vast array of packages tailored for data mining tasks.

This instructor-led live training in Portugal (online or onsite) is aimed at 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.

Unstructured data is estimated to constitute over 90% of all data, with a significant portion appearing as text. This volume continues to expand rapidly through blog posts, tweets, social media activity, and other digital publications.

This instructor-led, live course focuses on extracting valuable insights and meaning from this vast amount of information. By leveraging the R programming 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 within text data. Data samples are provided in various languages to meet specific customer needs.

Upon completion of this training, participants will be capable of preparing datasets (both large and small) from diverse sources and applying appropriate algorithms to analyze and report on their significance.

Format of the Course

• A blend of lectures and discussions, with a strong emphasis on hands-on practice and occasional assessments to evaluate understanding

Target Audience

Course Format

Upon completing this training, participants will be equipped to:

This instructor-led live training guides participants through the process of manipulating and visualizing data using the tools available in the Tidyverse.

The Tidyverse comprises a suite of versatile R packages designed for cleaning, processing, modelling, and visualizing data. Key packages include: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Individuals new to the R language
• Beginners in data analysis and data visualization

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

• Conduct data analysis and create compelling visualizations
• Derive meaningful insights from various datasets and sample data
• Filter, sort, and summarize data to address exploratory questions
• Transform processed data into informative line plots, bar plots, and histograms
• Import and filter data from diverse sources, including Excel, CSV, and SPSS files