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Program Syllabus

Advanced Microsoft Azure with AI

Build advanced cloud and AI skills using Microsoft Azure through hands-on, real-world learning. Learn how to design scalable cloud solutions, integrate AI capabilities, and manage modern Azure environments for enterprise applications.

  • Design and manage scalable cloud Azure cloud infrastructure and services

  • Work with Azure AI, Machine Learning, and intelligent cloud solutions

  • Build secure, data-driven cloud architectures using Azure services

  • Integrate AI capabilities such as vision, speech, and language into applications

  • Apply DevOps, security, governance, and automation practices in Azure environments

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Target Audience

  • Cloud and IT professionals advancing their Microsoft Azure and AI skills

  • Developers building AI-enabled cloud applications and services

  • Data and analytics professionals exploring Azure Machine Learning and AI solutions

  • Professionals preparing for cloud engineering, AI, or DevOps-focused roles

  • Technology professionals working with scalable cloud infrastructure and automation

  • Individuals interested in enterprise cloud and AI solution architecture

Advanced Microsoft Azure with AI Overview

Advanced Microsoft Azure with AI is a practical, industry-focused program designed to develop advanced cloud computing and AI skills using Microsoft Azure. Through hands-on learning and real-world scenarios, learners build the skills needed to design scalable cloud solutions, integrate AI capabilities, manage modern Azure environments, and support intelligent business applications.

  • Design and deploy scalable cloud solutions using Microsoft Azure

  • Work with Azure services for compute, storage, networking, databases, and AI

  • Build and deploy Machine Learning solutions using Azure AI and Azure Machine Learning

  • Integrate AI capabilities such as vision, speech, and language into applications

  • Apply security, governance, automation, and DevOps practices in Azure environments

  • Develop intelligent cloud applications for modern business and enterprise use cases

Delivered using OCA’s Skill Sprint™ Method with hands-on practice, real-world exercises, and instructor-led feedback.

Prerequisites

The following foundational skills are recommended to maximize learning outcomes:

  • Basic familiarity with cloud computing concepts and internet-based applications

  • Comfort using a computer (file navigation, browser usage, basic system operations)

  • Basic understanding of networking, databases, or IT concepts is helpful but not required

  • Interest in cloud technologies, artificial intelligence, and modern application development

  • Willingness to explore Microsoft Azure services and complete hands-on cloud exercises

Outcomes

By the end of this course, you will be able to:

  • Understand advanced Microsoft Azure architecture and enterprise cloud concepts

  • Deploy and manage Azure compute, storage, networking, and cloud resources

  • Build and manage data pipelines using Azure data services

  • Integrate AI capabilities such as vision, speech, and language into applications

  • Develop and deploy Machine Learning solutions using Azure Machine Learning

  • Design intelligent cloud solutions that combine AI, data, and scalable infrastructure

  • Apply security, identity management, governance, and monitoring practices in Azure

  • Understand DevOps and CI/CD workflows used in modern cloud environments

  • Optimize cloud applications for performance, scalability, and reliability

  • Build practical Azure and AI solutions for real-world business scenarios

Job Roles & Careers

After completing the training, learners will be better prepared for positions such as:

  • Cloud Engineer

  • Azure Cloud Engineer

  • AI Solutions Engineer

  • Cloud Application Developer

  • Azure Infrastructure Specialist

  • Machine Learning Engineer (Azure Environments)

  • Cloud Operations Engineer

  • DevOps and Cloud Automation Associate

  • Azure Solutions Consultant

Curriculum

Learn through focused Skill Sprints built around practical application and real-world tasks.

  • Understand Azure cloud architecture and service categories

  • Use Azure Resource Manager (ARM) and resource groups

  • Organize cloud workloads and resources efficiently

  • Prepare Azure environments for development and deployment

  • Navigate Azure portal and management tools

  • Deploy Azure Virtual Machines and App Services

  • Configure Azure Functions for serverless workloads

  • Manage Azure Storage and data services

  • Implement Azure networking components

  • Select the appropriate Azure services for different workloads

  • Work with Azure AI and Cognitive Services

  • Integrate vision, speech, and language capabilities into applications

  • Build AI-enabled workflows using Azure services

  • Understand Machine Learning workflows in Azure environments

  • Evaluate business scenarios for AI-powered cloud solutions

  • Work with Azure Cognitive Services capabilities

  • Apply Computer Vision and image recognition services

  • Use speech recognition and language AI services

  • Implement Natural Language Processing solutions

  • Build AI-powered decision and automation workflows

  • Build ETL and data integration workflows using Azure Data Factory

  • Integrate multiple data sources for analytics and AI workloads

  • Manage structured and unstructured data using Azure data services

  • Prepare datasets for Machine Learning solutions

  • Apply data transformation and preparation techniques

  • Build and train Machine Learning models using Azure ML Studio

  • Evaluate model performance and accuracy

  • Apply model tuning and optimization techniques

  • Deploy Machine Learning models into cloud environments

  • Understand MLOps and model lifecycle management concepts

  • Integrate AI APIs into application workflows

  • Design architecture for intelligent cloud applications

  • Apply AI features in real application scenarios

  • Develop AI-enabled cloud solutions

  • Evaluate performance of intelligent applications

  • Apply Azure security and governance best practices

  • Manage identity and access using Microsoft Entra ID

  • Implement authentication and access control policies

  • Understand governance, compliance, and security monitoring concepts

  • Protect cloud applications, services, and data resources

  • Understand DevOps workflows in Azure environments

  • Build CI/CD pipelines for cloud applications

  • Monitor cloud services and application performance

  • Optimize Azure applications for scalability and reliability

  • Manage deployment and application lifecycle processes

Design and implement an intelligent cloud solution using Microsoft Azure by integrating cloud infrastructure, data pipelines, Machine Learning models, and AI services to solve a real-world business problem.

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$1,499   

  • Instructor-Led: Live Online

  • 48 Total Hours

  • Advanced Level

  • Real-World Project

  • Career-Focused

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Why This Course Is in Demand

Cloud computing and artificial intelligence are becoming essential technologies across modern business and enterprise environments. Organizations are increasingly using Microsoft Azure to build scalable cloud solutions, manage data-driven applications, and integrate AI capabilities into modern digital systems.

This course helps professionals build advanced Azure, cloud, and AI integration skills for modern cloud engineering, application development, and intelligent technology environments.

Frequently Asked Questions

This course is ideal for IT professionals, developers, cloud engineers, and students who want to build advanced skills in Microsoft Azure and artificial intelligence. It is also suitable for professionals looking to transition into cloud computing, AI engineering, or modern application development roles.

Basic familiarity with cloud computing or IT concepts is helpful but not mandatory. The course begins with Azure environment setup and progressively builds toward advanced topics such as AI services, machine learning, and intelligent application development.

Participants learn how to deploy and manage Azure infrastructure, work with data services, build machine learning models using Azure Machine Learning, integrate Azure Cognitive Services, and develop intelligent cloud applications. The course also covers security, governance, and DevOps practices used in modern Azure environments.

This course supports roles such as Cloud Engineer, Azure Cloud Engineer, AI Solutions Engineer, Machine Learning Engineer, Cloud Application Developer, Azure DevOps Engineer, and Cloud Solutions Architect (associate level).

Yes. The program is designed to support working professionals who want to upgrade their cloud and AI skills. The structured Skill Sprint Method™ enables efficient learning with guided instruction and practical exercises.

The total duration is 48 hours, consisting of 24 hours of instructor-led live sessions and 24 hours of guided practice, exercises, and case-based discussions. This structure ensures a balance between conceptual learning and practical application.

Yes. The course is delivered as an instructor-led online program in a live virtual classroom format where participants can interact with instructors, ask questions, and complete guided exercises.

The course focuses on Microsoft Azure services including Azure Virtual Machines, Azure Storage, Azure Data Factory, Azure SQL Database, Azure Machine Learning, Azure Cognitive Services, and Azure DevOps tools used for cloud deployment and application delivery.

Yes. Participants who successfully complete the course and final project will receive a Certificate of Completion from OCA.

Yes. Corporate and group training programs are available and can be customized to align with organizational cloud adoption, AI integration, and workforce upskilling goals.

Registration can be completed through the course page on the OCA website or by contacting the admissions team for enrollment assistance, schedules, and upcoming cohorts.

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