AI-900: Microsoft Azure AI Fundamentals

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This course is an introduction to artificial intelligence (AI) concepts and services on Microsoft Azure, focusing on practical use cases rather than deep technical programming.
Students will learn the basics of machine learning, computer vision, natural language processing, and conversational AI, along with how these services can be implemented on Azure.
Perfect for business users, project managers, or anyone who needs a foundational understanding of AI and its real-world applications — with no coding required.

Module 1 – Introduction to AI

• Define artificial intelligence and common AI workloads
• Explore guiding principles for responsible AI at Microsoft
• Understand real-world applications of AI across industries

Module 2 – Machine Learning on Azure

• Introduction to machine learning concepts (models, training, inference)
• Explore Azure Machine Learning Studio and its no-code capabilities
• Understand supervised, unsupervised, and reinforcement learning

Module 3 – Computer Vision

• Analyze images and video using Azure Computer Vision APIs
• Build image classification and object detection scenarios
• Explore facial recognition, form recognition, and video analysis services

Module 4 – Natural Language Processing (NLP)

• Understand key NLP capabilities: sentiment analysis, key phrase extraction, translation
• Use Azure Language Services for document summarization and text analytics
• Build simple language understanding models with no coding

Module 5 – Conversational AI

• Introduction to building chatbots with Azure Bot Services
• Explore integration with Microsoft Teams and custom web apps
• Understand bot development lifecycle (design, build, test, publish)

Ideal for:

• Business managers and project leads evaluating AI solutions
• Students or early-career professionals exploring AI technologies
• Functional consultants and decision-makers in digital transformation roles
• Organizations aiming to integrate AI into their business operations
   

• Basic familiarity with Microsoft Azure is helpful but not required
• No programming or data science expertise necessary
• Curiosity about AI technologies and their real-world impact recommended

This practical course teaches learners how to develop, integrate, and optimize generative AI solutions using the Azure OpenAI Service.
Students will explore large language models (LLMs) like GPT, Codex, and DALL-E, learn effective prompt engineering, and integrate AI capabilities into real-world applications — all with minimal coding.
Perfect for solution architects, developers, and business innovators who want to harness the power of Azure’s generative AI safely, responsibly, and efficiently.

Module 1 – Introduction to Azure OpenAI Service

• Understand Azure OpenAI Service capabilities and available models (GPT, Codex, DALL-E)
• Learn about security, compliance, and responsible AI use
• Set up an Azure OpenAI environment

Module 2 – Working with Azure OpenAI Models

• Deploy models for text generation, code generation, and image creation
• Understand completions, chat completions, embeddings APIs
• Use low-code tools and REST APIs for model integration

Module 3 – Prompt Engineering for Generative AI

• Design effective prompts to guide model behavior
• Apply techniques like few-shot prompting, system messages, chaining prompts
• Optimize outputs for business tasks (summarization, classification, creative writing)

Module 4 – Building and Integrating Generative AI Solutions

• Integrate AI models into applications with Logic Apps, Power Automate, and Azure Functions
• Build AI-driven chatbots and virtual agents
• Develop solutions responsibly with content filtering and monitoring

Module 5 – Governance, Security, and Responsible Deployment

• Implement security, privacy, and compliance controls
• Apply Responsible AI principles in solution design
• Monitor model usage, costs, and optimize API consumption
   

Ideal for:

• Solution architects and developers building AI-enhanced app
• Business innovators implementing generative AI capabilities
• Technology decision-makers planning enterprise AI strategy
• Organizations wanting secure, scalable generative AI integration
   

• Familiarity with Azure basics (resource groups, APIs, portals) recommended
• Basic understanding of AI and machine learning concepts helpful
• No advanced coding required — low-code tools and simple API usage emphasized

This in-depth course teaches learners how to design, build, manage, and deploy AI solutions using Microsoft Azure AI services.
Students will gain hands-on experience with computer vision, natural language processing, conversational AI, and knowledge mining — leveraging Azure Cognitive Services and Azure Machine Learning.
Perfect for AI developers, solution architects, and data engineers aiming to create enterprise-grade AI applications with Azure's low-code and scalable tools.

Module 1 – Introduction to Azure AI Services

• Understand Azure Cognitive Services portfolio
• Overview of Azure Machine Learning, Azure Bot Service, and Knowledge Mining
• Set up Azure AI resources and SDKs

Module 2 – Implementing Computer Vision Solutions

• Analyze images and videos using Computer Vision and Custom Vision
• Build image classification and object detection models
• Apply OCR (Optical Character Recognition) and spatial analysis

Module 3 – Developing Natural Language Processing Solutions

• Analyze text for sentiment, key phrases, language translation
• Build custom language understanding models with Language Studio
• Apply Azure Language Service for document intelligence

Module 4 – Building Conversational AI Solutions

• Design and create chatbots using Azure Bot Service and Language Studio
• Integrate bots with Microsoft Teams and web apps
• Implement dialog flows, QnA Maker, and orchestration

Module 5 – Knowledge Mining with Azure Cognitive Search

• Build search experiences over unstructured data
• Integrate AI enrichment for key phrase extraction, entity recognition
• Implement custom skills for document indexing

Module 6 – Integrating AI Models into Applications

• Call Azure AI services from custom apps via REST APIs and SDKs
• Secure, monitor, and manage AI services in production environments
• Apply responsible AI practices across the solution lifecycle

Ideal for:

• AI developers and software engineers
• Solution architects designing AI-enabled systems
• Data engineers building intelligent apps
• Professionals pursuing the Microsoft Certified: Azure AI Engineer Associate certification
   

• Knowledge of Azure fundamentals (AZ-900 recommended)
• Experience with basic programming concepts (C#, Python, or REST APIs)
• Familiarity with AI and machine learning concepts beneficial

This hands-on training prepares learners to build and operationalize machine learning solutions on Microsoft Azure.
Learners will explore Azure Machine Learning Studio, train and evaluate models, automate ML pipelines, and deploy scalable ML models — using a mix of low-code tools and basic Python.
Perfect for data scientists, AI developers, and analytics professionals seeking to become Azure Machine Learning Engineers or prepare for the Microsoft Certified: Azure Data Scientist Associate (DP-100) exam.

Module 1 – Introduction to Azure Machine Learning

• Explore Azure Machine Learning (Azure ML) Studio
• Understand workspaces, datasets, compute targets
• Set up resources for ML development

Module 2 – Preparing Data for Modeling

• Load and transform datasets
• Visualize and analyze data quality
• Engineer features for ML models

Module 3 – Building and Training Machine Learning Models

• Train models using AutoML and designer pipelines (low-code options)
• Understand model evaluation metrics
• Train custom models using Python SDK (optional — can focus on no-code Designer tools if avoiding coding)

Module 4 – Automating Machine Learning Workflows

• Create ML pipelines with Azure ML
• Manage training, testing, deployment workflows
• Enable reproducibility and tracking of experiments

Module 5 – Deploying and Managing Models

• Register, deploy, and consume models
• Implement model monitoring and retraining
• Manage deployments with real-time and batch inference

Module 6 – Responsible AI and Governance

• Apply fairness, interpretability, and transparency
• Secure ML solutions and implement compliance strategies

Ideal for:

• Data scientists and AI engineers
• Data analysts expanding into machine learning
• AI developers building Azure-based ML solutions
• Professionals aiming for the DP-100 certification
   

• Completion of AI-900 (Azure AI Fundamentals) is recommended
• Familiarity with core concepts in machine learning and statistics
• Some experience with Python scripting (optional — Azure ML Designer enables no-code/low-code work)
• Basic knowledge of Azure services like storage, compute, and networking

This hands-on training prepares learners to design, implement, and manage end-to-end analytics solutions using Microsoft Fabric, the unified data platform from Microsoft.
From building Lakehouses and Real-Time Analytics environments to integrating with Power BI for reporting, this course provides practical skills through real-world labs.
Perfect for data engineers, BI professionals, and analytics developers ready to master Microsoft's next-generation unified data platform.

Module 1 – Introduction to Microsoft Fabric

• Overview of Fabric architecture: Lakehouses, Warehouses, Real-Time Analytics
• Understand OneLake, Workspaces, and Fabric capacity
• Explore integration with Power BI, Data Factory, and Azure services

Module 2 – Ingesting and Preparing Data

• Load structured and unstructured data into Lakehouses
• Use Dataflows Gen2 and Pipelines for ETL/ELT
• Transform data using Spark notebooks and Power Query (no-code/low-code options)

Module 3 – Managing and Securing Data in Fabric

• Implement row-level security and access control
• Apply data governance with Purview integration
• Optimize storage and manage Fabric capacity

Module 4 – Building Analytical Models

• Create SQL Endpoints on Lakehouses and Warehouses
• Build data marts and datasets for analysis
• Understand Data Modeling and Star Schema design in Fabric

Module 5 – Enabling Real-Time and Advanced Analytics

• Stream and analyze real-time data using Real-Time Analytics hubs
• Integrate streaming and batch data
• Prepare datasets for Power BI or external AI/ML services

Module 6 – Visualizing and Sharing Insights

• Connect Fabric datasets to Power BI
• Build dynamic reports and dashboards
• Share insights securely inside and outside the organization

Ideal for:

• Data Engineers and Analytics Engineers
• Power BI Developers upgrading to Fabric environments
• Data Architects building unified data platforms
• Professionals seeking to implement scalable analytics on Microsoft Fabric
   

• Completion of Azure Fundamentals (AZ-900) or Data Fundamentals (DP-900) recommended
• Familiarity with data processing, SQL, and BI concepts helpful
• No heavy programming required — low-code/no-code tools emphasized where possible

This practical training teaches learners how to implement and manage Microsoft Dynamics 365 Field Service solutions to deliver on-site service experiences.
Learners will gain hands-on skills with resource scheduling, work order management, AI-driven dispatching, and Connected Field Service (IoT) integration.
Perfect for business analysts, service managers, and functional consultants seeking to optimize service delivery using Dynamics 365 technologies — with low-code configuration and no coding required. 

Module 1 – Introduction to Dynamics 365 Field Service

• Overview of Field Service capabilities and core entities
• Understand service organizations, customer assets, and agreements
• Set up a basic Field Service environment

Module 2 – Managing Work Orders

• Create and manage work orders and service tasks
• Configure service accounts, incidents, and pricing
• Define products, services, and billing arrangements

Module 3 – Scheduling and Dispatching Resources

• Configure the Universal Resource Scheduling (URS) system
• Use the Scheduling Board and Resource Scheduling Optimization (RSO)
• Enable AI-assisted dispatching for efficiency

Module 4 – Field Service Mobility and Connected Field Service

• Set up mobile app access for field technicians
• Integrate IoT devices with Connected Field Service
• Automate work order creation from device alerts

Module 5 – Managing Assets, Agreements, and Preventive Maintenance

• Configure asset management and preventive maintenance plans
• Manage customer assets across the service lifecycle
• Automate recurring work orders

Module 6 – Field Service Analytics and Reporting

• Set up dashboards, KPIs, and reports in Field Service
• Track service metrics and optimize performance
• Use Power BI integration for deeper analysis
   

Ideal for:

• Field service managers and dispatchers
• Dynamics 365 consultants and business analysts
• Solution architects designing service solutions
• Organizations aiming to optimize field operations with AI and IoT
   

• Basic understanding of Microsoft Dynamics 365 apps recommended
• Familiarity with customer service processes helpful
• No programming or software development experience required (configuration and low-code solutions focus)

 This hands-on training teaches learners how to design, create, secure, and manage solutions built with the Microsoft Power Platform — including Power Apps, Power Automate, and Power Virtual Agents.
Students will learn to create low-code business applications, automate workflows, build chatbots, and integrate AI into business processes.
Perfect for app makers, business analysts, citizen developers, and IT professionals aiming to leverage Power Platform to drive digital transformation — with no heavy coding required. 

Module 1 – Introduction to the Power Platform

• Overview of Power Apps, Power Automate, Power BI, and Power Virtual Agents
• Explore key components: Dataverse, Connectors, AI Builder
• Understand Power Platform security and governance basics

Module 2 – Building Model-Driven and Canvas Apps

• Create model-driven apps using Dataverse
• Build canvas apps with drag-and-drop controls
• Configure forms, views, and dashboards

Module 3 – Automating Business Processes with Power Automate

• Design cloud flows for business automation
• Implement instant, scheduled, and approval flows
• Integrate AI into flows using AI Builder

Module 4 – Creating Intelligent Virtual Agents

• Build chatbots using Power Virtual Agents
• Integrate bots with Microsoft Teams and websites
• Automate common service interactions and FAQs

Module 5 – Managing Solutions and Environments

• Package apps and flows into solutions
• Configure environments, security roles, and permissions
• Use ALM (Application Lifecycle Management) best practices

Module 6 – Extending Power Platform Solutions

• Integrate external data sources
• Add Power BI visualizations to apps
• Connect Power Platform apps to Azure services (optional, minimal coding)

Ideal for:

• Citizen developers and business users
• Business analysts and app makers
• Functional consultants designing no-code/low-code solutions
• Organizations seeking to accelerate innovation without traditional coding
   

• Basic understanding of Microsoft 365 apps (Outlook, Teams, SharePoint)
• No prior app development or coding experience required
• Familiarity with business processes is helpful for automation scenarios

This hands-on training prepares learners to analyze data, create powerful reports, and deliver actionable insights using Microsoft Power BI.
Students will learn to model, transform, visualize, and share data effectively, connecting multiple sources to uncover hidden business value.
Perfect for business analysts, data professionals, and anyone responsible for turning data into critical business insights — with a focus on drag-and-drop modeling and DAX formulas, not heavy coding. 

Module 1 – Preparing Data for Analysis

• Connect to various data sources (Excel, databases, cloud services)
• Cleanse, transform, and load data using Power Query Editor
• Handle missing or inconsistent data

Module 2 – Modeling Data

• Design data models using relationships and hierarchies
• Build calculated columns, measures, and KPIs with DAX
• Optimize models for performance and usability

Module 3 – Visualizing Data

• Create interactive reports with built-in and custom visuals
• Apply formatting, filtering, and slicing techniques
• Use bookmarks and tooltips for advanced storytelling

Module 4 – Analyzing Data

• Perform trend analysis, clustering, forecasting
• Leverage Q&A visual and natural language queries
• Build what-if parameters and dynamic insights

Module 5 – Managing and Sharing Insights

• Publish reports and dashboards to the Power BI Service
• Set up workspaces, apps, and secure access
• Schedule data refreshes and automate report updates

Module 6 – Power BI Administration and Governance (Optional)

• Understand licensing, capacity planning, and tenant settings
• Monitor usage and optimize performance
• Apply data security best practices (RLS, sensitivity labels)
   

Ideal for:

• Business analysts and reporting specialists
• Data professionals looking to deliver insights
• Functional consultants integrating analytics into business solutions
• Decision-makers aiming to improve organizational intelligence
   

• Basic understanding of business data concepts (tables, relationships)
• Familiarity with Microsoft Excel and formulas helpful
• No programming experience required — DAX is formula-based, similar to Excel expressions

This hands-on course teaches learners how to implement and manage a Customer Data Platform (CDP) solution using Microsoft Dynamics 365 Customer Insights.
Students will gain practical skills in ingesting customer data, unifying profiles, segmenting audiences, applying AI-driven insights, and maintaining data governance.
Perfect for data analysts, customer experience specialists, and CRM consultants responsible for turning customer data into meaningful business intelligence — with a focus on configuration and no coding required.

Module 1 – Introduction to Customer Insights and CDP Concepts

• Understand the role of a Customer Data Platform (CDP)
• Explore Customer Insights capabilities and integration points
• Set up the Customer Insights environment

Module 2 – Ingesting and Unifying Customer Data

• Connect and import data from multiple sources
• Map, match, and unify customer records
• Resolve identities and create customer profiles

Module 3 – Segmenting and Enriching Customer Data

• Define and build customer segments
• Apply enrichment using demographic, firmographic, and external data
• Personalize profiles with calculated measures

Module 4 – Activating Customer Insights Across Channels

• Export segments to marketing, sales, and customer service apps
• Integrate Customer Insights with Dynamics 365, Power Platform, and third-party systems
• Design action-triggering automations based on customer behavior

Module 5 – Using AI to Drive Deeper Insights

• Set up predictive models (churn prediction, product recommendation)
• Apply AI templates and custom scoring models
• Interpret and visualize AI-driven insights

Module 6 – Governing, Securing, and Monitoring Customer Data

• Apply data privacy rules and GDPR compliance strategies
• Set up security roles and manage environment access
• Monitor usage and optimize performance
   

Ideal for:

• Customer experience managers and analysts
• CRM and Dynamics 365 consultants
• Marketing technologists and data-driven marketers
• Organizations building AI-driven customer engagement strategies
   

• Familiarity with Dynamics 365 applications recommended
• Understanding of basic data concepts (tables, relationships, fields)
• No programming experience required — configuration-based platform

This practical training teaches learners how to build and deploy AI-powered applications using Copilot capabilities inside Microsoft Power Platform.
Students will explore how to integrate generative AI into Power Apps, Power Automate, and Power Virtual Agents, allowing them to create intelligent, responsive solutions without extensive coding.
Perfect for Power Platform developers, solution architects, and business users ready to leverage Copilot AI features to enhance app innovation and productivity.

Module 1 – Introduction to Copilot Capabilities in Power Platform

• Understand Copilot functionality across Power Apps, Power Automate, and Power Virtual Agents
• Overview of AI-assisted app and workflow building
• Explore integration with Dataverse and Microsoft AI services

Module 2 – Building AI-Enhanced Power Apps

• Use Copilot to generate apps based on natural language descriptions
• Enhance apps with AI suggestions for forms, data sources, and relationships
• Customize Copilot-driven apps without manual coding

Module 3 – Automating Workflows with Copilot in Power Automate

• Create cloud flows using conversational design
• Automate business processes quickly with AI-generated suggestions
• Refine and extend AI-suggested flows

Module 4 – Building Intelligent Chatbots with Copilot in Power Virtual Agents

• Develop conversational bots faster using Copilot-assisted authoring
• Integrate bots with Dynamics 365, Teams, and other channels
• Leverage AI-driven conversation analysis

Module 5 – Managing and Securing Copilot Solutions

• Set up environments, security roles, and permissions for Copilot apps and flows
• Apply responsible AI practices and content moderation settings
• Monitor Copilot usage and performance
   

Ideal for:

• Power Platform developers and app makers
• Business analysts and citizen developers
• Functional consultants building AI-enhanced solutions
• Organizations adopting low-code AI-driven business transformation
   

• Familiarity with Microsoft Power Platform (Power Apps, Power Automate, Power Virtual Agents)
• Basic understanding of business applications and processes
• No programming or AI expertise required — focus is on low-code/no-code AI development

This practical course teaches learners how to design, create, secure, and automate business solutions using Microsoft Power Platform — specifically Power Apps, Power Automate, and Power BI.
Students will learn how to build low-code apps, automate workflows, and visualize data to modernize business processes — all without needing formal programming knowledge.
Perfect for business users, functional consultants, and citizen developers seeking to solve business challenges quickly and efficiently.

Module 1 – Introduction to the Power Platform

• Understand Power Platform components (Power Apps, Power Automate, Power BI, Dataverse)
• Explore use cases for apps, workflows, and analytics
• Set up environments and connections

Module 2 – Building Canvas and Model-Driven Apps

• Design canvas apps using a drag-and-drop approach
• Create model-driven apps linked to Dataverse data
• Use expressions, formulas, and control properties

Module 3 – Automating Business Processes with Power Automate

• Create flows for approvals, notifications, and data integration
• Build instant, scheduled, and triggered flows
• Integrate flows into Power Apps

Module 4 – Visualizing and Analyzing Data with Power BI

• Connect Power Apps and Dataverse to Power BI
• Build interactive dashboards and visual reports
• Share insights across Microsoft Teams and SharePoint

Module 5 – Managing App Development and Solutions

• Package apps, flows, and data into solutions
• Set up Application Lifecycle Management (ALM) best practices
• Manage permissions, environments, and security settings
   

Ideal for:

• Business analysts and process owners
• Functional consultants and citizen developers
• Power Platform solution architects
• Organizations encouraging low-code/no-code innovation
   

• Basic familiarity with Microsoft 365 apps (Excel, Teams, SharePoint) helpful
• No prior programming experience required
• Understanding business processes and workflows is beneficial

This hands-on training teaches learners how to configure, secure, and manage Microsoft 365 Copilot across their organization.
Students will learn how to enable Copilot for Microsoft 365 apps (Word, Excel, Outlook, Teams), manage licensing, enforce security and compliance policies, and monitor Copilot usage — all through administrative portals and no coding required.
Perfect for IT administrators, Microsoft 365 admins, and security professionals ready to support the deployment and governance of Copilot within the enterprise.

Module 1 – Introduction to Microsoft 365 Copilot Administration

• Overview of Copilot capabilities in Microsoft 365 apps
• Understand licensing, prerequisites, and initial setup steps
• Explore Copilot in Word, Excel, Outlook, and Teams

Module 2 – Preparing Microsoft 365 Environment for Copilot

• Configure Microsoft Graph connectors
• Set up Microsoft 365 services integration for Copilot
• Manage data access, sensitivity labels, and security controls

Module 3 – Enabling and Managing Copilot Access

• Assign licenses and manage user access to Copilot
• Configure policies for different user groups
• Customize Copilot settings in the Microsoft 365 Admin Center

Module 4 – Security, Compliance, and Responsible AI

• Apply DLP (Data Loss Prevention) policies and Insider Risk Management for Copilot content
• Implement Responsible AI practices for safe deployment
• Enable auditing and monitoring for Copilot activities

Module 5 – Monitoring and Reporting Copilot Usage

• Track user adoption, feature usage, and satisfaction
• Generate reports with Microsoft 365 usage analytics
• Optimize licensing and security settings based on insights
   

Ideal for:

• Microsoft 365 Administrators and IT Managers
• Security Engineers managing cloud productivity tools
• Compliance Officers ensuring Responsible AI use
• Organizations deploying Copilot across Microsoft 365 environments

• Familiarity with Microsoft 365 administration portals (Admin Center, Security & Compliance Center)
• Understanding of Microsoft identity management (Azure AD/Entra ID)
• No programming experience required — admin configuration and governance focus