CA, Sunnyvale - Downtown Sunnyvale

640 W California Ave Suite 210, Sunnyvale, united states, 94086

The Sunnyvale center is located one block from Caltrain rail station and provides easy access to Central Expressway and Highway 101. It is in walking distance to the city's downtown district, featuring numerous restaurants, shops, and businesses, as well as a short drive from San Jose International Airport.

CA, San Francisco - Golden Gate

75 Broadway, San Francisco , united states, 94111

With its fabulous arched windows, the 75 Broadway office, located in the heart of Jackson Square, is designed to impress. Situated at Golden Gateway Commons on the second floor of this unique campus-style building, it overlooks the green terrain's of Sydney Walton Park with the famous waterfront piers behind. This enviable location is a short walk from public transport and just blocks away from the Embarcadero and the ferry building, as well as a host of convenient amenities.

Subcategories (1)

Azure Service Fabric

Azure Service Fabric

Explore Our Courses

Generative AI with Azure OpenAI for Java Developers

 14 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Terraform on Microsoft Azure

 21 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Building AI Cloud Apps with Microsoft Azure

 35 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Azure Synapse Analytics

 14 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Azure Data Lake Storage Gen2

 14 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Azure Cloud Security Basic to Advanced

 35 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Kubernetes on Azure (AKS)

 14 Hours
In this instructor-led, live training in San Francisco Bay Area (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.
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AI-102T00: Designing and Implementing a Microsoft Azure AI Solution

 28 Hours
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.
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AZ-400T00-A: Designing and Implementing Microsoft DevOps solutions

 35 Hours
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
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Azure Machine Learning (AML)

 21 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Architecting Microsoft Azure Solutions

 14 Hours
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.
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Azure DevOps Fundamentals

 14 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Azure Machine Learning

 14 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Azure Cloud Security

 7 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Building Microservices with Microsoft Azure Service Fabric (ASF)

 21 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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Developing Intelligent Bots with Azure

 14 Hours
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
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Introduction to Azure

 7 Hours
In this instructor-led, live training in San Francisco Bay Area (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
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Programming for IoT with Azure

 14 Hours
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.
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Kubeflow on Azure

 28 Hours
This instructor-led, live training in San Francisco Bay Area (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.
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MLOps for Azure Machine Learning

 14 Hours
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.
Read more...

Microsoft Azure Infrastructure and Deployment

 35 Hours
Microsoft Azure Infrastructure and Deployment
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Testimonials (8)

I loved the technical aspects of the exercises - it was great seeing Terraform in action and being able to see the creation of the resources in Azure.

Brett Hawson - Reach Plc

Course - Terraform on Microsoft Azure

It was very much what we asked for—and quite a balanced amount of content and exercises that covered the different profiles of the engineers in the company who participated.

Arturo Sanchez - INAIT SA

Course - Microsoft Azure Infrastructure and Deployment

I've got to try out resources that I've never used before.

Daniel - INIT GmbH

Course - Architecting Microsoft Azure Solutions

The Exercises

Khaled Altawallbeh - Accenture Industrial SS

Course - Azure Machine Learning (AML)

very friendly and helpful

Aktar Hossain - Unit4

Course - Building Microservices with Microsoft Azure Service Fabric (ASF)

The practical part, I was able to perform exercises and to test the Microsoft Azure features

Alex Bela - Continental Automotive Romania SRL

Course - Programming for IoT with Azure

Practical part and interaction with students

Piotr Madej - EY Global Services (Poland) Sp. z o.o.

Course - Azure DevOps Fundamentals

Learning about Kubernetes.

Felix Bautista - SGS GULF LIMITED ROHQ

Course - Kubernetes on Azure (AKS)

Upcoming Courses

Azure Data Lake Storage Gen2

2025-05-14 9:30 am
14 hours
CA, San Francisco - Golden Gate
$ 2703 (Online)
$ 3703 (Classroom)

Introduction to Azure

2025-05-28 9:30 am
7 hours
CA, Sunnyvale - Downtown Sunnyvale
$ 1630 (Online)
$ 2130 (Classroom)

Building AI Cloud Apps with Microsoft Azure

2025-06-16 9:30 am
35 hours
CA, San Francisco - Golden Gate
$ 6757 (Online)
$ 9257 (Classroom)

Azure Machine Learning

2025-06-25 9:30 am
14 hours
CA, Sunnyvale - Downtown Sunnyvale
$ 2703 (Online)
$ 3703 (Classroom)

Azure Data Lake Storage Gen2

2025-07-09 9:30 am
14 hours
CA, San Francisco - Golden Gate
$ 2703 (Online)
$ 3703 (Classroom)

Introduction to Azure

2025-07-23 9:30 am
7 hours
CA, Sunnyvale - Downtown Sunnyvale
$ 1630 (Online)
$ 2130 (Classroom)

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