Kubernetes on Azure (AKS) Training Course

This instructor-led, live training in US Empire (online or onsite) is aimed at engineers who wish to utilize Azure ML's intuitive drag-and-drop platform to deploy Machine Learning workloads without the need to purchase additional software and hardware, or manage maintenance and deployment tasks.

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

• Develop highly accurate machine learning models using Python, R, or no-code tools.
• Leverage Azure’s extensive data sets and algorithms to train and track machine learning and deep-learning models.
• Utilize Azure’s collaborative workspace to develop ML models in a team environment.
• Select from various Azure-supported ML frameworks, including PyTorch, TensorFlow, and scikit-learn.

This training is designed to enhance the capabilities of engineers working on government projects by providing them with the tools and knowledge necessary for effective machine learning deployment and management.

Microsoft Azure Infrastructure and Deployment for Government

This training enables participants to enhance their Microsoft Azure solution design skills for government.

Upon completion of this training, participants will understand the features and capabilities of Azure services, enabling them to identify trade-offs and make informed decisions for designing public and hybrid cloud solutions for government.

Throughout the training, participants will define the appropriate infrastructure and platform solutions to meet the required functional, operational, and deployment requirements through the solution life-cycle for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists who wish to utilize Azure Machine Learning to develop comprehensive machine learning models for predictive analysis.

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

• Construct machine learning models without prior programming experience.
• Develop predictive algorithms using Azure Machine Learning.
• Deploy production-ready machine learning algorithms for government use.

This instructor-led, live training in US Empire (online or onsite) is aimed at security administrators who wish to enhance the security of Azure workloads for government.

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

• Manage host security, network security, and other critical aspects.
• Configure storage and database security within Azure.
• Utilize Azure resources to implement robust security monitoring.
• Prevent malicious cyber attacks on data and infrastructure for government operations.

This instructor-led, live training in US Empire (online or onsite) is aimed at developers who wish to learn how to build microservices on Microsoft Azure Service Fabric (ASF) for government.

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

• Utilize ASF as a platform for building and managing microservices in alignment with public sector workflows.
• Gain an understanding of key microservices programming concepts and models relevant to government applications.
• Establish a cluster in Azure that meets the governance and accountability standards required for government operations.
• Deploy microservices both on-premises and in the cloud, ensuring compliance with government IT policies.
• Effectively debug and troubleshoot live microservice applications to maintain high levels of performance and reliability for government use.

The Azure Bot Service integrates the capabilities of the Microsoft Bot Framework and Azure Functions to facilitate the rapid development of intelligent bots for government.

In this instructor-led, live training, participants will learn how to efficiently create an intelligent bot using Microsoft Azure.

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

• Understand the fundamentals of intelligent bots
• Learn how to develop intelligent bots using cloud applications for government
• Gain proficiency in using the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Comprehend the design principles of bots through bot patterns
• Create their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the Course

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

DO180 is an introductory course on containers, Kubernetes fundamentals, and Red Hat OpenShift platform concepts, designed to build hands-on skills for government professionals.

This instructor-led, live training (available online or onsite) is targeted at beginner to intermediate-level technical professionals who wish to gain expertise in container workflows, Kubernetes primitives, and the deployment and operation of applications on OpenShift.

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

• Construct and manage container images and registries using best practices for reproducibility and security.
• Deploy and manage Kubernetes objects such as pods, deployments, and services within OpenShift environments.
• Leverage OpenShift features, including routes, buildconfigs, and the web console, to enhance application delivery processes.
• Implement persistent storage solutions, configuration management, and secrets handling for stateful workloads.
• Apply fundamental security measures, role-based access control (RBAC), and monitoring practices to ensure the health and integrity of clusters and applications.

Format of the Course

• Interactive lectures and discussions tailored for government participants.
• Hands-on labs in a live OpenShift environment conducted each day.
• Scenario-driven exercises and troubleshooting workshops to reinforce learning.

Course Customization Options

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

This instructor-led, live training in US Empire (online or onsite) is designed for engineers who wish to utilize Helm to streamline the process of installing and managing Kubernetes applications for government.

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

• Install and configure Helm for use in government environments.
• Create reproducible builds of Kubernetes applications that align with public sector workflows.
• Share applications as Helm charts, ensuring compliance with governance standards.
• Run third-party applications saved as Helm charts, while maintaining accountability and security.
• Manage releases of Helm packages in a manner that supports government operations.

In this instructor-led, live training in US Empire (onsite or remote), participants will gain a comprehensive understanding of the fundamental concepts, components, and services of Microsoft Azure as they work through the development of a sample cloud application for government use.

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

• Understand the foundational aspects of Microsoft Azure
• Familiarize themselves with the various Azure tools and services
• Acquire the skills necessary to leverage Azure for building cloud applications for government

The Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure offers a comprehensive set of cloud services, including an IoT Suite with preconfigured solutions designed to help developers accelerate the development of IoT projects for government.

In this instructor-led, live training, participants will learn how to develop IoT applications using Azure.

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

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Learn the benefits of using Azure in programming IoT systems for government
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

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.

This instructor-led, live training in US Empire (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to the Azure cloud for government use.

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

• Install and configure Kubernetes, Kubeflow, and other necessary software on Azure.
• Utilize Azure Kubernetes Service (AKS) to streamline the process of initializing a Kubernetes cluster on Azure for government operations.
• Create and deploy a Kubernetes pipeline for automating and managing ML models in production environments for government applications.
• Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel, enhancing efficiency for government projects.
• Leverage other AWS managed services to extend an ML application's capabilities for government use cases.

This instructor-led, live training in US Empire (online or onsite) is aimed at beginner-level to intermediate-level software developers and DevOps professionals who wish to learn how to set up and manage a local Kubernetes environment using Minikube for government.

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

• Install and configure Minikube on their local machine.
• Understand the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for developing, testing, and debugging applications in a government context.

This instructor-led, live training in US Empire (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to incorporate Minikube into their development workflows for government projects.

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

• Configure and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and troubleshoot applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines for government initiatives.
• Leverage Minikube's advanced features to optimize their development process for government use cases.
• Implement best practices for local Kubernetes development in a public sector context.

This instructor-led, live training (online or onsite) is aimed at machine learning engineers who wish to utilize Azure Machine Learning and Azure DevOps to implement MLOps practices for government.

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

• Construct reproducible workflows and machine learning models.
• Manage the entire machine learning lifecycle effectively.
• Track and report on model version history, assets, and other relevant data.
• Deploy production-ready machine learning models in any environment.