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.

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

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.

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 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.

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 instructor-led, live training in Radom (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level developers and technical professionals who wish to use Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a working agent, connect agents to business knowledge sources, evaluate and prepare agents for deployment.

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.

Azure Bot Service brings together the capabilities of the Microsoft Bot Framework and Azure Functions, providing a powerful platform for quickly building intelligent bots.

In this instructor-led, live training, participants will explore how to efficiently develop intelligent bots using Microsoft Azure.

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

Understand the core concepts behind intelligent bots.

Build intelligent bots using cloud-based applications.

Gain practical knowledge of the Microsoft Bot Framework, the Bot Builder SDK, and Azure Bot Service.

Apply established bot design patterns in real-world scenarios.

Create and deploy their first intelligent bot using Microsoft Azure.

Audience

This course is designed for developers, hobbyists, engineers, and IT professionals interested in bot development.

Format of the course

The training combines lectures and discussions with exercises and a strong emphasis on 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

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.

Course Description

This training is conducted live with 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 transform your approach to managing IT infrastructure.

What Will You Learn During the Training?

Prepare for an in-depth exploration of Terraform. Starting from an introduction to the IaC philosophy, you will learn the basics of HCL (HashiCorp Configuration Language) syntax, all the way to advanced techniques for state management and module creation. You will discover how Terraform fits into CI/CD processes and how to integrate it into your environment. Finally, you will learn the most important best practices and patterns that will help you write efficient, secure, and scalable Terraform code.

Is This Training for You?

Whether you are a programmer, system administrator, DevOps engineer, or simply a technology enthusiast, this training 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 Does the Training Work?

This is not just a regular training. It's an experience. Each day is structured to build a solid foundation and then build on that with more advanced skills. Starting from theory, we quickly move to practice where you will have the opportunity to apply your newfound knowledge. We are always here to answer your questions and help you understand every aspect of Terraform.

What Are the Prerequisites?

You need a computer with Windows and WSL, along with Visual Studio Code, or a Linux or MacOS system with Visual Studio Code. Basic knowledge of Git and the ability to navigate the console/terminal are also required.

Why Should You Participate in This Training?

Elevate your infrastructure management skills with our Terraform and IaC training. Not only will you learn new skills, but it will 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 a part of the future of infrastructure management.

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.