Kubernetes on Azure (AKS) Training Course

This instructor-led, live training in [location] (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 for purchasing software and hardware or managing maintenance and deployment. By the end of this training, participants will be able to: - Develop highly accurate machine learning models using Python, R, or zero-code tools. - Utilize Azure’s extensive data sets and algorithms to train and track machine learning and deep-learning models. - Collaborate effectively in Azure's interactive workspace for developing ML models. - Select from a variety of Azure-supported ML frameworks, including PyTorch, TensorFlow, and scikit-learn, to meet specific project requirements. This training is designed to enhance the capabilities of engineers working on government projects by providing them with the skills necessary to leverage Azure ML efficiently.

Microsoft Azure provides robust infrastructure and deployment solutions for government agencies. These services are designed to support scalable, secure, and efficient operations that align with public sector workflows, governance, and accountability requirements. Azure's infrastructure ensures high availability and reliability, while its deployment tools facilitate seamless integration and management of resources, enhancing overall operational effectiveness for government use.

This training enables participants to enhance their Microsoft Azure solution design skills. 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 functional, operational, and deployment requirements throughout the solution lifecycle.

This instructor-led, live training in US (online or onsite) is designed for government data scientists who wish to utilize Azure Machine Learning to develop end-to-end machine learning models for predictive analysis. By the end of this training, participants will be able to: - Construct machine learning models without programming experience. - Develop predictive algorithms using Azure Machine Learning. - Deploy production-ready machine learning algorithms for government applications.

This instructor-led, live training (available online or onsite) is designed for government security administrators who wish to secure Azure workloads. By the end of this training, participants will be able to: - Manage host security, network security, and other critical areas. - Configure storage and database security within Azure. - Utilize Azure resources to implement effective security monitoring. - Protect against malicious cyber attacks on data and infrastructures for government operations.

This instructor-led, live training in US (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 governmental systems.
• Comprehend key microservices programming concepts and models relevant to public sector applications.
• Establish a cluster in Azure tailored for government workflows.
• Deploy microservices on premises or in the cloud, ensuring alignment with governmental IT standards.
• Debug and troubleshoot live microservice applications to maintain high levels of service reliability for government operations.

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, with a focus on practical, hands-on skills development.

This instructor-led, live training (available both online and onsite) is designed for beginner to intermediate technical professionals who are interested in learning container workflows, Kubernetes basics, and how to deploy and operate applications on OpenShift.

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

• Build 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.
• Leverage OpenShift features like routes, build configurations, and the web console to enhance application delivery.
• Implement persistent storage, configuration management, and secrets handling for stateful workloads.
• Apply basic security measures, role-based access control (RBAC), and monitoring practices to ensure healthy clusters and applications.

Course Format

• Interactive lectures and discussions.
• Hands-on labs in a live OpenShift environment each day.
• Scenario-driven exercises and troubleshooting workshops.

Customization Options for Government

• To request a customized training tailored to the specific needs of your agency, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for engineers who wish to use 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. - Create reproducible builds of Kubernetes applications. - Share applications as Helm charts. - Run third-party applications saved as Helm charts. - Manage releases of Helm packages.

In this instructor-led, live training in US (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 devices and software applications wirelessly, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure provides 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 for government. 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 for government. **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 [location] (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to the Azure cloud for government. By the end of this training, participants will be able to: - Install and configure Kubernetes, Kubeflow, and other necessary software on Azure. - Use Azure Kubernetes Service (AKS) to streamline the initialization of a Kubernetes cluster on Azure. - Create and deploy a Kubernetes pipeline for automating and managing ML models in production environments. - Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel. - Leverage other Azure managed services to extend an ML application, ensuring alignment with public sector workflows and governance.

This instructor-led, live training in US (online or onsite) is designed for government software developers and DevOps professionals at the beginner to intermediate level who wish to learn how to set up and manage a local Kubernetes environment using Minikube. 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 for government use. - Deploy and manage containers using kubectl and the Minikube dashboard. - Set up persistent storage and networking solutions for Kubernetes in a government context. - Utilize Minikube for developing, testing, and debugging applications for government projects.

This instructor-led, live training (online or onsite) is designed for intermediate-level developers and DevOps engineers who wish to incorporate Minikube into their development workflows for government. By the end of this training, participants will be able to: - Set up and manage a local Kubernetes environment using Minikube. - Understand how to deploy, manage, and debug applications on Minikube. - Integrate Minikube into their continuous integration and deployment pipelines for government. - Optimize their development process using Minikube's advanced features. - Apply best practices for local Kubernetes development in alignment with public sector standards.

This instructor-led, live training (available online or onsite) is designed for government machine learning engineers who wish to utilize Azure Machine Learning and Azure DevOps to implement MLOps practices. By the end of this training, participants will be able to: - Construct reproducible workflows and machine learning models. - Manage the entire machine learning lifecycle. - Track and report on model version history, assets, and other relevant data. - Deploy production-ready machine learning models in any environment for government use.