Virtualization Management using Red Hat CloudForms Training Course

This instructor-led, live training in US Empire (online or onsite) is aimed at advanced-level professionals who wish to enhance their knowledge of machine learning models, improve their skills in hyperparameter tuning, and learn how to deploy models effectively using Google Colab for government.

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

• Implement advanced machine learning models using popular frameworks such as Scikit-learn and TensorFlow.
• Optimize model performance through hyperparameter tuning techniques.
• Deploy machine learning models in real-world applications utilizing Google Colab for government.
• Collaborate and manage large-scale machine learning projects within the Google Colab environment for government.

This instructor-led, live training in US Empire (onsite or remote) is aimed at engineers who wish to deploy and manage Internet of Things (IoT) devices on Amazon Web Services (AWS).

By the end of this training, participants will be able to construct an IoT platform that includes the deployment and management of a backend, gateway, and devices using AWS, aligning with best practices for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to create applications for various devices for government use.

By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices, ensuring alignment with public sector workflows and governance.

This instructor-led, live training in US Empire (onsite or remote) is designed for developers who wish to leverage AWS Lambda to build and deploy services and applications to the cloud, without the need to provision the execution environment (servers, VMs, containers, availability, scalability, storage, etc.).

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

• Configure AWS Lambda for government to execute a function.
• Understand FaaS (Functions as a Service) and the advantages of serverless development in public sector workflows.
• Build, upload, and execute AWS Lambda functions tailored for government applications.
• Integrate Lambda functions with various event sources relevant to government operations.
• Package, deploy, monitor, and troubleshoot Lambda-based applications to ensure compliance with governance and accountability standards.

This instructor-led, live training in US Empire (online or onsite) is designed for beginner-level data scientists and IT professionals who wish to gain foundational knowledge in data science using Google Colab for government.

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

• Set up and navigate Google Colab effectively.
• Write and execute basic Python code.
• Import and manage datasets efficiently.
• Create visualizations using Python libraries to support data-driven decision-making for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab for government.

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

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development for government applications.
• Implement image preprocessing techniques for computer vision tasks in a public sector context.
• Deploy computer vision models for real-world, government-specific applications.
• Use transfer learning to enhance the performance of CNN models for government projects.
• Visualize and interpret the results of image classification models in a manner that supports public sector decision-making.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.

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

• Set up and navigate Google Colab for government deep learning projects.
• Understand the foundational principles of neural networks.
• Implement deep learning models using TensorFlow.
• Train and evaluate deep learning models effectively.
• Utilize advanced features of TensorFlow to enhance deep learning applications for government use.

This instructor-led, live training in US Empire (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9 for government.

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

• Set up and configure AWS Cloud9 for efficient DevOps workflows in a public sector environment.
• Implement continuous integration and continuous delivery (CI/CD) pipelines that align with government standards and requirements.
• Automate testing, monitoring, and deployment processes using AWS Cloud9 to enhance governance and accountability.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows to support public sector operations.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9 to ensure compliance with government policies and procedures.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda for government.

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

• Understand the fundamentals of serverless architecture for government use cases.
• Set up AWS Cloud9 for developing serverless applications tailored to public sector needs.
• Develop, test, and deploy serverless applications using AWS Lambda in alignment with government workflows.
• Integrate AWS Lambda with other AWS services such as API Gateway and S3 to support government operations.
• Optimize serverless applications for performance and cost efficiency in a government context.

This instructor-led, live training in US Empire (online or onsite) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualizations for government.

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

• Set up and navigate Google Colab for data visualization in a government context.
• Create various types of plots using Matplotlib to support public sector workflows.
• Utilize Seaborn for advanced visualization techniques that align with government standards.
• Customize plots to enhance presentation and clarity in government reports.
• Interpret and present data effectively using visual tools that ensure accountability and transparency for government audiences.

Summary:

• Fundamentals of Internet of Things (IoT) architecture and functions for government.
• Understanding "things," sensors, the internet, and their alignment with business functions in IoT applications.
• Essential components of IoT software: hardware, firmware, middleware, cloud services, and mobile applications for government use.
• Key IoT functionalities including fleet management, data visualization, Software as a Service (SaaS)-based fleet management and data visualization, alerts and alarms, sensor onboarding, device onboarding, and geofencing for government operations.
• Basics of IoT device communication with the cloud using MQTT protocol for government applications.
• Connecting IoT devices to AWS with MQTT through AWS IoT Core for government projects.
• Integrating AWS IoT Core with AWS Lambda functions for computation and data storage in government environments.
• Linking Raspberry Pi to AWS IoT Core and facilitating simple data communication for government use cases.
• Managing alerts and events in IoT systems for government operations.
• Calibrating sensors for accurate data collection in government applications.

Summary:

• Fundamentals of Internet of Things (IoT) architecture and functionality
• Understanding the roles of “things,” sensors, internet connectivity, and their alignment with business functions in IoT systems
• Essential components of IoT software, including hardware, firmware, middleware, cloud services, and mobile applications
• Key IoT functionalities such as fleet management, data visualization, Software-as-a-Service (SaaS) based solutions for fleet management and data visualization, alerts/alarms, sensor onboarding, device onboarding, and geofencing
• Basic principles of IoT device communication with the cloud using MQTT protocol
• Connecting IoT devices to AWS with MQTT through AWS IoT Core
• Integrating AWS IoT Core with AWS Lambda for computation and data storage using DynamoDB
• Linking a Raspberry Pi to AWS IoT Core for simple data transmission
• Practical exercises with Raspberry Pi and AWS IoT Core to develop a smart device
• Data visualization and communication via web interfaces for government applications

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level data scientists and developers who wish to apply machine learning algorithms efficiently using the Google Colab environment for government.

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

• Set up and navigate Google Colab for machine learning projects in a public sector context.
• Understand and apply various machine learning algorithms relevant to government workflows.
• Utilize libraries like Scikit-learn to analyze and predict data for government applications.
• Implement supervised and unsupervised learning models aligned with public sector objectives.
• Optimize and evaluate machine learning models effectively to support government decision-making processes.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level data scientists and developers who aim to apply natural language processing (NLP) techniques using Python within Google Colab.

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

• Grasp the fundamental concepts of natural language processing.
• Prepare and clean text data for NLP tasks.
• Conduct sentiment analysis using the NLTK and SpaCy libraries.
• Utilize Google Colab for scalable and collaborative development, tailored specifically for government use cases.

This instructor-led, live training in US Empire (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab for government applications.

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

• Understand the fundamentals of the Python programming language.
• Implement Python code within the Google Colab environment.
• Utilize control structures to manage the flow of a Python program effectively.
• Develop functions to organize and reuse code efficiently.
• Explore and utilize basic libraries for Python programming in public sector workflows.