Neural Network in R Training Course

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.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly adopted by managers and data analysts in both the corporate and academic sectors. Additionally, R has 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 is largely attributed to the expanding use of data mining for various objectives, including setting advertising prices, accelerating drug discovery, and refining financial models. R offers a comprehensive array of packages specifically tailored for data mining applications, 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 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

This instructor-led, live training in US (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. It is increasingly utilized by managers and data analysts in both the corporate sector and academic institutions. R offers a broad range of packages that facilitate data mining, making it a valuable tool for government and other public sector applications.

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 available in two formats: online instruction and discussion, or face-to-face workshops.

R is an open-source programming language designed for statistical computing, data analysis, and generating graphics. It is increasingly utilized by managers and data analysts in both corporate and academic environments. R has also gained traction among statisticians, engineers, and scientists who may lack formal computer programming skills due to its user-friendly nature. The growing popularity of R can be attributed to the expanding use of data mining for various objectives, such as setting advertisement prices, accelerating drug discovery, or refining financial models. R offers a broad range of packages tailored for data mining applications. This course provides comprehensive instruction on manipulating objects in R, including reading data, accessing R packages, writing R functions, and creating informative graphs. It covers the analysis of data using common statistical models. Participants will learn to use the R software (https://www.r-project.org) both through command-line interfaces and graphical user interfaces (GUIs). This training is designed to enhance data analysis capabilities for government and other public sector workflows, ensuring alignment with governance and accountability standards.

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.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly adopted by managers and data analysts in both the public and private sectors, including academia. R has also gained popularity among statisticians, engineers, and scientists who may not have extensive computer programming skills due to its user-friendly nature. The rising demand for data mining across various fields, such as setting advertisement prices, accelerating drug discovery, or refining financial models, has contributed to R's growing use. R offers a comprehensive array of packages specifically tailored for data mining, enhancing its utility and versatility for government and other organizational needs.

This course is designed for data scientists and statisticians who already possess fundamental R and C++ coding skills and are looking to enhance their advanced R programming abilities. The objective is to provide a practical, advanced R programming course for participants interested in applying these methods in their professional roles. Sector-specific examples are utilized to ensure the training is pertinent to the audience, aligning with the needs of professionals working in various fields, including those for government.

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 designed for cleaning, processing, modeling, and visualizing data. Key packages include ggplot2, dplyr, tidyr, readr, purrr, and tibble. - **Target Audience:** - Beginners to the R language - Beginners to data analysis and data visualization - **Course Format:** - Part lecture, part discussion, exercises, and extensive hands-on practice - **Learning Objectives:** - Perform data analysis and create compelling visualizations - Draw meaningful conclusions from various datasets of sample data - Filter, sort, and summarize data to answer exploratory questions - Transform processed data into informative line plots, bar plots, and histograms - Import and filter data from a variety of sources, including Excel, CSV, and SPSS files This training is designed to equip participants with the skills necessary for effective data manipulation and visualization, aligning with the needs and standards required for government data analysis.

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.