Architecting Microsoft Azure Solutions Training Course

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at engineers who wish to use Azure ML's drag-and-drop platform to deploy Machine Learning workloads without having to purchase software and hardware and without having to worry about maintenance and deployment.

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

• Write highly-accurate machine learning models using Python, R, or zero-code tools.
• Leverage Azure's available data sets and algorithms to train and track machine learning and deep-learning models.
• Use Azures interactive workspace to collaboratively develop ML models.
• Choose from different Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.

This course equips IT Professionals with the skills to manage their Azure subscriptions effectively, secure identities, administer infrastructure, configure virtual networking, establish connections between Azure and on-premises sites, manage network traffic, implement storage solutions, create and scale virtual machines, deploy web apps and containers, back up and share data, and monitor the overall solution.

This course is designed for Azure Administrators. The role of an Azure Administrator involves implementing, managing, and monitoring identity, governance, storage, compute, and virtual networks in a cloud environment. Azure Administrators are responsible for provisioning, sizing, monitoring, and adjusting resources as needed to ensure optimal performance.

This course is designed to help Solutions Architects translate business requirements into secure, scalable, and reliable solutions. It covers various topics such as virtualization, automation, networking, storage, identity management, security, data platforms, and application infrastructure. The course explains how decisions in each of these areas impact the overall solution.

Audience Profile

This course is intended for IT Professionals who have expertise in designing and implementing solutions on Microsoft Azure. Participants should have a broad understanding of IT operations, including networking, virtualization, identity management, security, business continuity, disaster recovery, data platforms, budgeting, and governance. Azure Solution Architects typically start with the Azure Portal and as they become more proficient, they transition to using the Command Line Interface. Candidates are expected to have expert-level skills in Azure administration and experience with Azure development processes and DevOps practices.

This one-day course will offer foundational knowledge on Azure concepts, core Azure services, and essential management tools. It will also cover general security measures, network security, governance, privacy, and compliance features, as well as cost management and service level agreements in Azure.

Note: This course does not provide an Azure pass or time for students to engage in hands-on labs. If you are looking for a more interactive and practical lab experience, consider the AZ-900T00: Microsoft Azure Fundamentals (2-day) course, which includes guided hands-on labs. The content of both courses aligns with the AZ-900 exam objectives.

Microsoft Azure Infrastructure and Deployment

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at DevOps engineers, developers, and project managers who wish to utilize Azure DevOps to build and deploy optimized enterprise applications faster than traditional development approaches.

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

• Understand the fundamental DevOps vocabulary and principles.
• Install and configure the necessary Azure DevOps tools for software development.
• Utilize Azure DevOps tools and services to continuously adapt to the market.
• Build enterprise applications and evaluate current development processes upon Azure DevOps solutions.
• Manage teams more efficiently and accelerate software deployment time.
• Adopt DevOps development practices within the organization.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at data scientists who wish to use Azure Machine Learning to build end-to-end machine learning models for predictive analysis.

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

• Build machine learning models with zero programming experience.
• Create predictive algorithms with Azure Machine Learning.
• Deploy production ready machine learning algorithms.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at security administrators who wish to secure Azure workloads.

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

• Administrate host security, network security, and more.
• Set up storage and database security in Azure.
• Implement security monitoring using Azure resources.
• Prevent malicious cyber attacks on data and infrastructures.

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

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

• Use ASF as a platform for building and managing microservices.
• Understand key microservices programming concepts and models.
• Create a cluster in Azure.
• Deploy microservices on premises or in the cloud.
• Debug and troubleshoot a live microservice application.

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

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 basics of intelligent bots
• Learn how to develop intelligent bots using cloud applications
• Gain insight into using the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Comprehend how to design bots using bot patterns
• Create their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

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

In this instructor-led, live training in Uzbekistan (onsite or remote) participants will learn the fundamental concepts, components, and services of Microsoft Azure as they step through the creation of a sample cloud application.

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

• Understand the basics of Microsoft Azure
• Understand the different Azure tools and services
• Learn how to use Azure for building cloud applications

The Internet of Things (IoT) is a network infrastructure that wirelessly connects physical objects and software applications, 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.

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 core principles of IoT architecture
• Install and configure the Azure IoT Suite
• Discover the advantages of using Azure for programming IoT systems
• Implement various Azure IoT services such as IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and 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 Uzbekistan (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to Azure cloud.

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

• Install and configure Kubernetes, Kubeflow and other needed software on Azure.
• Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
• Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
• Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
• Leverage other AWS managed services to extend an ML application.

In this instructor-led, live training in Uzbekistan (online or onsite), participants will learn how to set up and manage a production-scale container environment using Kubernetes on AKS. 

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

• Configure and manage Kubernetes on AKS.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Azure.
• Migrate an existing Kubernetes environment from on-premise to AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

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

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

• Build reproducible workflows and machine learning models.
• Manage the machine learning lifecycle.
• Track and report model version history, assets, and more.
• Deploy production ready machine learning models anywhere.