Predictive Modelling with R Training Course

In this instructor-led, live training in US Empire, participants will gain a comprehensive understanding of Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement agencies around the world will be examined to provide insights into their adoption approaches, challenges, and outcomes.

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

• Integrate Big Data technology with traditional data gathering methods to construct a coherent narrative during an investigation.
• Implement scalable big data storage and processing solutions for effective data analysis.
• Develop a proposal for the adoption of the most suitable tools and processes to enable a data-driven approach to criminal investigations, tailored specifically for government use.

Audience

If you are tasked with interpreting the data available to your agency or analyzing unstructured data from public sources (such as Twitter, LinkedIn, etc.), this course is for government professionals like you.

It is primarily designed for decision-makers and individuals who need to determine which data is worth collecting and analyzing within a governmental context.

While the course is not intended for those configuring the technical solutions, participants in these roles will still gain valuable insights into the broader picture of data management for government operations.

Delivery Mode

During the course, delegates will be presented with working examples of primarily open-source technologies that are relevant to public sector workflows and governance.

Short lectures will be followed by presentations and simple exercises to engage participants actively in the learning process.

Content and Software Used

All software used is updated each time the course is conducted, ensuring the use of the most current versions available.

The curriculum covers the entire data lifecycle, from acquisition and formatting to processing and analysis, with a focus on automating decision-making processes using machine learning techniques for government applications.

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists and data analysts who wish to automate, evaluate, and manage predictive models using DataRobot's machine learning capabilities for government.

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

• Load datasets in DataRobot to analyze, assess, and ensure data quality.
• Build and train models to identify key variables and achieve prediction targets.
• Interpret model outputs to generate actionable insights that support informed decision-making.
• Monitor and manage models to maintain optimal predictive performance.

• Understand the importance of ethics in AI development and deployment for government.

• Learn to identify and mitigate ethical risks associated with AI for government operations.

• Gain insights into regulatory and compliance requirements specific to the public sector.

• Develop strategies for fostering an ethical AI culture within government organizations.

Format of the Course

• Interactive lectures and discussions tailored to public sector needs.
• Extensive exercises and practice sessions designed for government applications.
• Hands-on implementation in a live-lab environment relevant to government workflows.

Course Customisation Options

• To request a customized training course for government, please contact us to arrange.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level developers who wish to build AI-powered applications using predictive analytics and generative models for government.

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

• Understand the foundational principles of predictive AI and generative models.
• Leverage AI-powered tools for predictive coding, forecasting, and automation in government workflows.
• Implement Large Language Models (LLMs) and transformers for text and code generation within public sector applications.
• Apply time-series forecasting and AI-based recommendations to enhance decision-making processes.
• Develop and fine-tune AI models for practical, real-world government applications.
• Evaluate ethical considerations and best practices in the deployment of AI technologies within government operations.

This instructor-led, live training in US Empire (online or onsite) is designed for beginner-level IT professionals who wish to understand the fundamentals of Predictive AI for government.

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

• Comprehend the core concepts of Predictive AI and their applications in public sector workflows.
• Gather, clean, and preprocess data for predictive analysis aligned with government standards.
• Explore and visualize data to uncover insights that support informed decision-making for government.
• Develop basic statistical models to make predictions relevant to public sector challenges.
• Assess the performance of predictive models to ensure accuracy and reliability in government operations.
• Apply Predictive AI concepts to real-world scenarios within the context of government services.

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.

Predictive analytics is a process that leverages data analytics to forecast future events. This approach combines data with data mining, statistical analysis, and machine learning techniques to develop predictive models.

In this instructor-led, live training, participants will learn how to use Matlab to construct predictive models and apply them to large datasets to anticipate future outcomes based on the data.

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

• Create predictive models to identify patterns in historical and transactional data
• Leverage predictive modeling to recognize risks and opportunities
• Develop mathematical models that capture significant trends
• Utilize data from devices and business systems to optimize processes, reduce waste, save time, or cut costs

Audience

• Developers
• Engineers
• Domain experts

Format of the course

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

This training is designed to enhance skills for government professionals and align with public sector workflows, governance, and accountability.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level data professionals who seek to apply machine learning techniques to address data-driven business challenges, including sales forecasting and predictive modeling using neural networks.

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

• Understand the fundamental concepts and types of machine learning for government applications.
• Apply key algorithms for classification, regression, clustering, and association analysis in a public sector context.
• Perform exploratory data analysis and data preparation using Python, tailored to meet the needs of government agencies.
• Use neural networks for nonlinear modeling tasks relevant to public sector workflows.
• Implement predictive analytics for business forecasting, including sales data, to support informed decision-making for government.
• Evaluate and optimize model performance using visual and statistical techniques to ensure accountability and transparency in government operations.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level DevOps professionals who seek to integrate predictive artificial intelligence into their DevOps practices.

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

• Implement predictive analytics models to anticipate and address challenges within the DevOps pipeline.
• Utilize AI-driven tools for advanced monitoring and operations.
• Apply machine learning techniques to enhance software delivery workflows.
• Develop AI strategies for proactive issue resolution and process optimization.
• Navigate the ethical considerations associated with using AI in DevOps environments, ensuring compliance and accountability for government.

RapidMiner is an open-source data science software platform designed for rapid application prototyping and development. It offers an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.

In this instructor-led, live training, participants will learn how to use RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models.

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

• Install and configure RapidMiner
• Prepare and visualize data using RapidMiner
• Validate machine learning models
• Integrate data sources and create predictive models
• Incorporate predictive analytics into business processes
• Troubleshoot and optimize RapidMiner for government applications

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

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

Note

• To request a customized training for this course, please contact us to arrange.

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.

This instructor-led, live training (online or onsite) is designed for government analysts, researchers, and professionals at the beginner to intermediate level who wish to utilize SPSS for data preparation, statistical analysis, and predictive modeling for government.

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