Azure Training in Radom

This instructor-led, live training in Radom (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 Radom (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 Radom (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 Radom (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 Radom (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 Radom (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 Radom (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.

During the "Introduction to Microsoft Azure and Azure Kubernetes Service" training, participants will acquire skills in creating applications in the Microsoft Azure cloud, using containerization (Docker) and service Azure Kubernetes Service (AKS). The course covers architecture Microsoft Azure, application hosting strategies, creating resource groups and configuring services. Participants will also learn modern application development practices using Git repository, containers Docker, CI/CD flows and AKS. The training will include practical implementation examples and concepts Docker, Kubernetes and integration with tools Azure DevOps.

This course teaches Solutions Architects how to translate business requirements into secure, scalable, and reliable solutions. Lessons include design considerations related to logging, cost analysis, authentication and authorization, governance, security, storage, high availability, and migration. This role requires decisions in multiple areas that affect an overall design solution.

Learn how to investigate, respond to, and hunt for threats using Microsoft Azure Sentinel, Azure Defender, and Microsoft 365 Defender. In this course you will learn how to mitigate cyberthreats using these technologies. Specifically, you will configure and use Azure Sentinel as well as utilize Kusto Query Language (KQL) to perform detection, analysis, and reporting. The course was designed for people who work in a Security Operations job role and helps learners prepare for the exam SC-200: Microsoft Security Operations Analyst. Audience Profile The Microsoft Security Operations Analyst collaborates with organizational stakeholders to secure information technology systems for the organization. Their goal is to reduce organizational risk by rapidly remediating active attacks in the environment, advising on improvements to threat protection practices, and referring violations of organizational policies to appropriate stakeholders. Responsibilities include threat management, monitoring, and response by using a variety of security solutions across their environment. The role primarily investigates, responds to, and hunts for threats using Microsoft Azure Sentinel, Azure Defender, Microsoft 365 Defender, and third-party security products. Since the Security Operations Analyst consumes the operational output of these tools, they are also a critical stakeholder in the configuration and deployment of these technologies. Job role: Security Engineer Preparation for exam: SC-200 Features: none Skills gained

• Explain how Microsoft Defender for Endpoint can remediate risks in your environment
• Create a Microsoft Defender for Endpoint environment
• Configure Attack Surface Reduction rules on Windows 10 devices
• Perform actions on a device using Microsoft Defender for Endpoint
• Investigate domains and IP addresses in Microsoft Defender for Endpoint
• Investigate user accounts in Microsoft Defender for Endpoint
• Configure alert settings in Microsoft Defender for Endpoint
• Explain how the threat landscape is evolving
• Conduct advanced hunting in Microsoft 365 Defender
• Manage incidents in Microsoft 365 Defender
• Explain how Microsoft Defender for Identity can remediate risks in your environment
• Investigate DLP alerts in Microsoft Cloud App Security
• Explain the types of actions you can take on an insider risk management case
• Configure auto-provisioning in Azure Defender
• Remediate alerts in Azure Defender
• Construct KQL statements
• Filter searches based on event time, severity, domain, and other relevant data using KQL
• Extract data from unstructured string fields using KQL
• Manage an Azure Sentinel workspace
• Use KQL to access the watchlist in Azure Sentinel
• Manage threat indicators in Azure Sentinel
• Explain the Common Event Format and Syslog connector differences in Azure Sentinel
• Connect Azure Windows Virtual Machines to Azure Sentinel
• Configure Log Analytics agent to collect Sysmon events
• Create new analytics rules and queries using the analytics rule wizard
• Create a playbook to automate an incident response
• Use queries to hunt for threats
• Observe threats over time with livestream

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language. Audience Profile Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

This course provides students with the fundamental knowledge and skills to use PowerShell for administering and automating administration of Windows servers. This course provides students the skills to identify and build the command they require to perform a specific task. In addition, students learn how to build scripts to accomplish advanced tasks such as automating repetitive tasks and generating reports. This course provides prerequisite skills supporting a broad range of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. In keeping with that goal, this course will not focus on any one of those products, although Windows Server, which is the common platform for all of those products, will serve as the example for the techniques this course teaches.

This course teaches Azure administrators how to plan, deliver, and manage virtual desktop experiences and remote apps, for any device, on Azure. Students will learn through a mix of demonstrations and hands-on lab experiences deploying virtual desktop experiences and apps on Azure Virtual Desktop and optimizing them to run in multi-session virtual environments.

This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms. Audience profile Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. Job role: DevOps Engineer Preparation for exam: AZ-400 Skills gained

• Plan for the transformation with shared goals and timelines
• Select a project and identify project metrics and Key Performance Indicators (KPI's)
• Create a team and agile organizational structure
• Design a tool integration strategy
• Design a license management strategy (e.g. Azure DevOps and GitHub users)
• Design a strategy for end-to-end traceability from work items to working software
• Design an authentication and access strategy
• Design a strategy for integrating on-premises and cloud resources
• Describe the benefits of using Source Control
• Describe Azure Repos and GitHub
• Migrate from TFVC to Git
• Manage code quality including technical debt SonarCloud, and other tooling solutions
• Build organizational knowledge on code quality
• Explain how to structure Git repos
• Describe Git branching workflows
• Leverage pull requests for collaboration and code reviews
• Leverage Git hooks for automation
• Use Git to foster inner source across the organization
• Explain the role of Azure Pipelines and its components
• Configure Agents for use in Azure Pipelines
• Explain why continuous integration matters
• Implement continuous integration using Azure Pipelines
• Define Site Reliability Engineering
• Design processes to measure end-user satisfaction and analyze user feedback
• Design processes to automate application analytics
• Manage alerts and reduce meaningless and non-actionable alerts
• Carry out blameless retrospectives and create a just culture
• Define an infrastructure and configuration strategy and appropriate toolset for a release pipeline and application infrastructure
• Implement compliance and security in your application infrastructure
• Describe the potential challenges with integrating open-source software
• Inspect open-source software packages for security and license compliance
• Manage organizational security and compliance policies
• Integrate license and vulnerability scans into build and deployment pipelines
• Configure build pipelines to access package security and license ratings

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.

About This Course This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth. Audience Profile The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful. At Course Completion After completing this course, you will be able to:

• Describe Artificial Intelligence workloads and considerations
• Describe fundamental principles of machine learning on Azure
• Describe features of computer vision workloads on Azure
• Describe features of Natural Language Processing (NLP) workloads on Azure
• Describe features of conversational AI workloads on Azure

This instructor-led, live training in Radom (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 IT Professionals how to manage their Azure subscriptions, secure identities, administer the infrastructure, configure virtual networking, connect Azure and on-premises sites, manage network traffic, implement storage solutions, create and scale virtual machines, implement web apps and containers, back up and share data, and monitor your solution. This course is for Azure Administrators. The Azure Administrator implements manages and monitors identity, governance, storage, compute, and virtual networks in a cloud environment. The Azure Administrator will provision, size, monitor, and adjust resources as appropriate.

About This Course This course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions. Audience Profile

• Students in this course are interested in Azure development or in passing the Microsoft Azure Developer Associate certification exam.

Skills gained

• Design a governance solution.
• Design a compute solution.
• Design an application architecture.
• Design storage, non-relational and relational.
• Design data integration solutions.
• Design authentication, authorization, and identity solutions.
• Design network solutions.
• Design backup and disaster recovery solutions.
• Design monitoring solutions.
• Design migration solutions.

This course provides IT Security Professionals with the knowledge and skills needed to implement security controls, maintain an organization’s security posture, and identify and remediate security vulnerabilities. This course includes security for identity and access, platform protection, data and applications, and security operations. Audience profile This course is for Azure Security Engineers who are planning to take the associated certification exam, or who are performing security tasks in their day-to-day job. This course would also be helpful to an engineer that wants to specialize in providing security for Azure-based digital platforms and play an integral role in protecting an organization's data. Skills gained

• Implement enterprise governance strategies including role-based access control, Azure policies, and resource locks.
• Implement an Azure AD infrastructure including users, groups, and multi-factor authentication.
• Implement Azure AD Identity Protection including risk policies, conditional access, and access reviews.
• Implement Azure AD Privileged Identity Management including Azure AD roles and Azure resources.
• Implement Azure AD Connect including authentication methods and on-premises directory synchronization.
• Implement perimeter security strategies including Azure Firewall.
• Implement network security strategies including Network Security Groups and Application Security Groups.
• Implement host security strategies including endpoint protection, remote access management, update management, and disk encryption.
• Implement container security strategies including Azure Container Instances, Azure Container Registry, and Azure Kubernetes.
• Implement Azure Key Vault including certificates, keys, and secretes.
• Implement application security strategies including app registration, managed identities, and service endpoints.
• Implement storage security strategies including shared access signatures, blob retention policies, and Azure Files authentication.
• Implement database security strategies including authentication, data classification, dynamic data masking, and always encrypted.
• Implement Azure Monitor including connected sources, log analytics, and alerts.
• Implement Azure Security Center including policies, recommendations, and just in time virtual machine access.
• Implement Azure Sentinel including workbooks, incidents, and playbooks.

This instructor-led, live training in Radom (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 Radom (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 Radom (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 Radom (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 Radom (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

About This Course In this course, students will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. Students will identify and describe core data concepts such as relational, non-relational, big data, and analytics, and explore how this technology is implemented with Microsoft Azure. They will explore the roles, tasks, and responsibilities in the world of data. The students will explore relational data offerings, provisioning and deploying relational databases, and querying relational data through cloud data solutions with Microsoft Azure. They will explore non-relational data offerings, provisioning and deploying non-relational databases, and non-relational data stores with Microsoft Azure. Students will explore the processing options available for building data analytics solutions in Azure. They will explore Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Students will learn what Power BI is, including its building blocks and how they work together. Audience Profile The audience for this course is individuals who want to learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build their foundational knowledge of cloud data services within Microsoft Azure. At Course Completion After completing this course, students will be able to:

• Describe core data concepts in Azure
• Explain concepts of relational data in Azure
• Explain concepts of non-relational data in Azure
• Identify components of a modern data warehouse in Azure

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 Radom (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.

This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.

Training description The training is conducted live with the participation of a trainer. It is not a video course! Discover the power of infrastructure as code! Let us guide you through the fascinating world of Infrastructure as Code (IaC) using one of the most innovative tools - Terraform. This four-day intensive training will equip you with practical skills that will change the way you manage your IT infrastructure. What will you learn during the training? Get ready to dive into deep knowledge of Terraform. Starting with an introduction to the IaC philosophy, you will learn the basics of HCL (HashiCorp Configuration Language) syntax, all the way to advanced state management and module creation techniques. You will learn how Terraform fits into CI/CD processes, as well as how to implement it in your environment. Finally, you will learn the most important practices and patterns that will help you write efficient, secure, and scalable Terraform code. Is this training for you? Whether you are a developer, system administrator, engineer DevOps, or just a technology enthusiast, this course is for you. If you have basic knowledge of Git and the ability to navigate the console or terminal, you are ready to start your journey with Terraform. How is the training carried out? This is not just a training session. This is an experience. Each day is designed to give you a solid foundation and then build on it with more advanced skills. Starting with theory, we quickly move into practice, where you will have the opportunity to apply what you have learned. We are always here to answer your questions and help you understand every aspect Terraform. What are the entry requirements? You need a Windows machine with WSL and Visual Studio Code, or a Linux or macOS machine with Visual Studio Code. Basic knowledge of Git and the ability to navigate the console/terminal is also required. Why is it worth attending this training? Take your infrastructure management to the next level with our Terraform and IaC training. It will not only teach you new skills, but also open doors to new opportunities in your career. Understanding and using Terraform is becoming increasingly valued in the IT world. Join us and become part of the future of infrastructure management.

Trainer: Piotr Kośka

Piotr Kośka is an experienced infrastructure and security engineer with over a decade of experience in various IT technology fields. He currently works as a senior security and infrastructure engineer at Huuuge Games, where he leads the team and manages the AWS cloud infrastructure, CI/CD environment, as well as automation tools such as Ansible, Salt, Terraform and OpenTofu.

Piotr is the author of numerous publications that focus on various aspects of computer science, including securing home servers, as well as topics related to cloud computing and language Bash. His extensive experience includes working with many systems Linux, such as Ubuntu, Debian, CentOS and CoreOS, as well as server administration Jenkins and container management Docker and LXC/LXD.

This three-day course is intended primarily for IT Professionals who have experience with managing an on-premises Windows Server environment. Its purpose is to prepare professionals for planning, implementing, and managing environments that include Azure IaaS-hosted Windows Server-based workloads. The course covers how to leverage the hybrid capabilities of Azure, how to migrate virtual and physical server workloads to Azure IaaS, and how to manage and secure Azure VMs running Windows Server 2019.

Microsoft Azure Infrastructure and Deployment