Building Web Applications in R with Shiny Training Course

Big Data is a term that refers to solutions designed for storing and processing large data sets. Initially developed by Google, these Big Data solutions have since evolved and inspired other similar projects, many of which are available as open-source options for government use. R is a popular programming language in the financial industry.

R is an open-source programming language used for statistical computing, data analysis, and graphics. It is increasingly adopted by managers and data analysts within both the public and private sectors, as well as in academic institutions. R has also gained a following among statisticians, engineers, and scientists who may not have extensive computer programming skills but find it user-friendly. The language's popularity is attributed to its utility in various data mining applications, such as setting advertisement prices, accelerating drug discovery, and refining financial models. R offers a broad array of packages for data mining, making it a valuable tool for government and other sectors that rely on robust data analysis.

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

Audience

Developers and Data Analysts for government

Duration

3 days

Format

Lectures and Hands-on Practice

This instructor-led, live training in US Empire (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.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. R is increasingly utilized by managers and data analysts within both the corporate and academic sectors. It offers a broad array of packages for data mining, enhancing its utility for government applications and public sector workflows.

Audience

This course is designed for government business owners, including marketing managers, product managers, and customer base managers, along with their teams; it also caters to customer insights professionals.

Overview

The course follows the customer lifecycle from acquiring new customers to managing existing customers for profitability, retaining valuable customers, and understanding which customers are leaving and why. We will be working with real (if anonymized) data from a variety of sectors including telecommunications, insurance, media, and high tech, tailored to provide insights relevant for government.

Format

The course is instructor-led over five half-day sessions, incorporating in-class exercises as well as homework assignments. It can be delivered either in a classroom setting or through distance (online) learning, ensuring flexibility and accessibility for government participants.

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly utilized by managers and data analysts in both the corporate and academic sectors. R offers a comprehensive array of packages for data mining, making it a valuable tool for government and other public sector workflows.

Audience

• Managers for government
• Developers
• Scientists
• Students

Format of the Course

The course is offered in a flexible format, including online instruction and discussion or face-to-face workshops.

R is an open-source programming language for statistical computing, data analysis, and graphics. R is increasingly utilized by managers and data analysts within corporations and academic institutions. It has also gained popularity among statisticians, engineers, and scientists without extensive computer programming skills due to its user-friendly nature. The growing use of data mining for various objectives, such as setting advertisement prices, accelerating drug discovery, or refining financial models, has contributed to R's widespread adoption. R offers a comprehensive range of packages for data mining.

This course covers the manipulation of objects in R, including reading data, accessing R packages, writing R functions, and creating informative graphs. It also includes analyzing data using common statistical models. The course is designed to teach participants how to use the R software (https://www.r-project.org) both through a command line interface and via a graphical user interface (GUI). This training is tailored to enhance skills for government professionals and align with public sector workflows, governance, and accountability.

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly utilized by managers and data analysts within both the public and private sectors, as well as in academia. R has gained a following among statisticians, engineers, and scientists who may not have formal computer programming skills due to its user-friendly nature. The growing popularity of R is attributed to the increasing use of data mining for various objectives, such as setting advertisement prices, accelerating drug discovery, or refining financial models. R offers a comprehensive array of packages that support advanced data mining techniques, making it an essential tool for government and other sectors.

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly utilized by managers and data analysts within both the public and private sectors, including academia. R has also gained a following among statisticians, engineers, and scientists without extensive computer programming skills due to its user-friendly nature. Its growing popularity in various fields is attributed to the increasing reliance on data mining for diverse objectives, such as setting advertisement prices, accelerating drug discovery, or refining financial models. R offers a broad array of packages specifically tailored for data mining, making it an essential tool for government and other sectors.

This course provides an introduction to the application of neural networks in real-world scenarios, utilizing R-project software for government. It is designed to enhance the capabilities of professionals in addressing complex data challenges within public sector workflows.

This course is designed for data scientists and statisticians who already possess basic R and C++ coding skills and need to enhance their advanced R coding capabilities.

The purpose is to provide a practical, advanced R programming course for participants interested in applying these methods at work, specifically tailored for government.

Sector-specific examples are utilized to ensure the training is relevant to the audience.

This course is part of the Data Scientist skill set for government (Domain: Data and Technology).

Audience

Format of the Course

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

In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the key packages include: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and data visualization

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

• Perform data analysis and create informative visualizations
• Draw meaningful conclusions from various datasets of sample data
• Filter, sort, and summarize data to answer exploratory questions
• Transform processed data into insightful line plots, bar plots, histograms, and more
• Import and filter data from diverse sources, including Excel, CSV, and SPSS files, for government applications