Azure Training in Kazakhstan

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at intermediate-level Java developers, software engineers, and cloud enthusiasts who wish to harness the power of Azure OpenAI to create intelligent applications. By the end of this training, participants will be able to:

• Understand the principles of Generative AI and its applications.
• Set up and manage an Azure OpenAI service.
• Integrate OpenAI's models into Java applications.
• Deploy AI-powered features within web applications.

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at intermediate-level cloud engineers and IT professionals who wish to use Terraform to automate the deployment, management, and scaling of infrastructure on the Azure cloud platform. By the end of this training, participants will be able to:

• Understand the basics of Terraform and its benefits in infrastructure as code.
• Set up and configure Terraform for Azure.
• Develop, test, and deploy Terraform configuration files for various Azure services.
• Use Terraform for managing and scaling Azure resources.
• Implement best practices for Terraform state management and version control.
• Integrate Terraform with Azure DevOps for automated deployments.
• Create reusable Terraform modules for consistent resource provisioning.
• Utilize advanced features of Terraform for complex infrastructure deployments.

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to build and deploy AI-powered cloud applications using Microsoft Azure. By the end of this training, participants will be able to:

• Develop event-driven and serverless applications using Azure Functions.
• Manage Azure storage solutions and virtual machines.
• Deploy and scale web applications using Azure App Service and Docker containers.
• Integrate AI, machine learning, and natural language processing using Azure AI Services.
• Leverage GitHub Copilot to assist in AI-driven cloud application development.

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at intermediate-level data engineers who wish to become proficient in utilizing Azure Synapse Analytics for a wide range of data processing, analytics, and visualization. By the end of this training, participants will be able to:

• Understand the core concepts, architecture, and components of Azure Synapse Analytics.
• Create, configure, and manage scalable data warehouses using Azure Synapse.
• Master the techniques for ingesting, transforming, and loading data (ETL) from various sources into Azure Synapse.
• Optimize query performance, secure data, and integrate Azure Synapse with Power BI and other tools to visualize data and share insights.

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at intermediate-level data engineers who wish to learn how to use Azure Data Lake Storage Gen2 for effective data analytics solutions. By the end of this training, participants will be able to:

• Understand the architecture and key features of Azure Data Lake Storage Gen2.
• Optimize data storage and access for cost and performance.
• Integrate Azure Data Lake Storage Gen2 with other Azure services for analytics and data processing.
• Develop solutions using the Azure Data Lake Storage Gen2 API.
• Troubleshoot common issues and optimize storage strategies.

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at security administrators who wish to learn how to configure Azure cloud security to secure workloads running in Azure. By the end of this training, participants will be able to:

• Configure host and network security.
• Configure Azure advanced security options.
• Use Azure to secure cloud computing workloads.
• Use endpoint protection services security against malware and viruses.
• Secure container workloads that are running in Azure.

In this instructor-led, live training in Kazakhstan (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.

About This Course In this course, students will learn how to design and develop services that access local and remote data from various sources. Students will also learn how to develop and deploy services to hybrid environments, including on-premises servers and Microsoft Azure. Audience Profile Primary: .NET developers who want to learn how to develop services and deploy them to hybrid environments.
Secondary: .NET developers with Web application development experience who are exploring developing new applications or porting existing applications to Microsoft Azure. At Course Completion After completing this course, students will be able to:

• Describe the basic concepts of service development and data access strategies using the .NET platform.
• Describe the Microsoft Azure cloud platform and its compute, data, and application hosting offerings.
• Design and develop a data-centric application using Visual Studio 2017 and Entity Framework Core.
• Design, implement, and consume HTTP services using ASP.NET Core.
• Extend HTTP services using ASP.NET Core.
• Host services on-premises and in Microsoft Azure.
• Deploy services to both on-premises and cloud environments and manage the interface and policy for their services.
• Choose a data storage solution, cache, distribute, and synchronize data.
• Monitor, log, and troubleshoot services.
• Describe claim-based identity concepts and standards, and implement authentication and authorization with Azure Active Directory.
• Create scalable service applications.

Gain the necessary knowledge for designing Azure AI solution by building a customer support chat Bot using artificial intelligence from the Microsoft Azure platform including language understanding and pre-built AI functionality in the Azure Cognitive Services.

This instructor-led, live training in Kazakhstan (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.

About This Course This two-day course is designed for AWS Sysops administrators interested in learning how Azure is different from AWS, and how Azure is administered. The workshops main topics are Azure Administration, Azure Networking, Azure Compute, Azure Storage, and Azure Governance. This workshop combines lecture with hands-on practical exercises and discussion/review. During the workshop students will build an end-to-end architecture that demonstrates the main features discussed in the course. Audience Profile The audience for this course is an AWS Sysops Administrator Associate or equivalent. This person has one to two years of experience in AWS deployment, management, and operations. Students taking this course are interested in learning how Azure is different from AWS, and how Azure is administered. Students may also be interested in taking the AZ-103 Microsoft Azure Administrator certification exam, or the AZ-900 Azure Fundamentals exam.

About This Course A three-day course designed to teach AWS (Amazon Web Services) developers how to prepare end-to-end solutions in Microsoft Azure. In this course you will construct Azure App Service Web App solutions and Azure Functions, use blob or Cosmos DB storage in solutions, implement secure cloud solutions that include user authentication and authorization, implement API management, and develop event- and message-based solutions, and monitor, troubleshoot, and optimize your Azure solutions. You will learn how developers use Azure services, with additional focus on features and tasks that differ from AWS, and what that means for you as you develop applications that will be hosted by using Azure services. Audience Profile Students in this course are experienced AWS developers interested in Azure development.

This course teaches Solutions Architects how to translate business requirements into secure, scalable, and reliable solutions. Lessons include virtualization, automation, networking, storage, identity, security, data platform, and application infrastructure. This course outlines how decisions in each of these areas affect an overall solution. Audience profile This course is for IT Professionals with expertise in designing and implementing solutions running on Microsoft Azure. They should have broad knowledge of IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platform, budgeting, and governance. Azure Solution Architects use the Azure Portal and as they become more adept they use the Command Line Interface. Candidates must have expert-level skills in Azure administration and have experience with Azure development processes and DevOps processes.

This instructor-led, live training in Kazakhstan (online or onsite) is aimed at beginner-level IT professionals who wish to learn about Microsoft Azure and cloud computing. By the end of this training, participants will be able to:

• Understand basic cloud concepts.
• Identify core Azure services.
• Describe core solutions and management tools in Azure.
• Understand general security and network security features.
• Understand identity, governance, privacy, and compliance features.
• Understand Azure cost management and Service Level Agreements (SLAs).

This training permits delegates to improve their Microsoft Azure solution design skills. After this training the delegate will understand the features and capabilities of Azure services, to be able to identify trade-offs, and make decisions for designing public and hybrid cloud solutions. During training the appropriate infrastructure and platform solutions to meet the required functional, operational, and deployment requirements through the solution life-cycle will be defined.

This instructor-led, live training in Kazakhstan (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 Kazakhstan (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 Kazakhstan (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 Kazakhstan (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 combines the power of the Microsoft Bot Framework and Azure functions to enable rapid development of intelligent bots. In this instructor-led, live training, participants will learn how to easily create an intelligent bot using Microsoft Azure By the end of this training, participants will be able to:

• Learn the fundamentals of intelligent bots
• Learn how to create intelligent bots using cloud applications
• Understand how to use the Microsoft Bot Framework, the Bot Builder SDK, and the Azure Bot Service
• Understand how to design bots using bot patterns
• Develop their first intelligent bot using Microsoft Azure

Audience

• Developers
• Hobbyists
• Engineers
• IT Professionals

Format of the course

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

About This Course This course will enable the students to understand Azure SQL Database, and educate the students on what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. Audience Profile The primary audience for this course is database developers who plan to migrate their MySQL or Postgres DB workloads to Azure SQL DB. The secondary audience for this course is MySQL/Postgres administrators to raise awareness of the features and benefits of Azure SQL DB. At Course Completion At the end of this course, the students will have learned:

• Migrate on-premises MySQL to Azure SQL DB for MySQL
• Migrate on-premises PostgreSQL to Azure SQL DB for PostgreSQL

In this instructor-led, live training in Kazakhstan (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

Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, allowing them to communicate with each other and exchange data via network communications, cloud computing, and data capture. Azure is a comprehensive set of cloud services which offers an IoT Suite consisting of preconfigured solutions that help developers accelerate 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 fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Learn the benefits of using Azure in programming IoT systems
• 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 heavy hands-on practice

Note

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

This instructor-led, live training in Kazakhstan (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.

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.

Microsoft Azure Infrastructure and Deployment