Architecting agentic AI business solutions is an advanced course for architects, senior consultants, and technical leaders responsible for planning, designing, and governing AI-powered enterprise solutions built on Microsoft platforms. This course serves as a foundational, real-world, and architectural preparation step that builds the design judgment, strategic reasoning, and end-to-end understanding learners need before pursuing the AB-100 exam or implementing agentic AI solutions at scale. Learners will explore how to architect AI-powered business solutions that use agents, copilots, and generative AI to automate tasks, improve decision-making, and enhance employee and customer experiences. Emphasis is placed on architecture, trade-offs, governance, cost/benefit analysis, and lifecycle management, rather than step-by-step configuration.

This course teaches learners how to design, configure, and govern AI-enhanced sales solutions using Dynamics 365 Sales, Microsoft Copilot, and AI agent capabilities to support sellers across the lead-to-cash process. Learners translate business requirements into practical, AI-first seller workflows that improve productivity, forecasting accuracy, and decision-making while aligning with organizational revenue goals, governance standards, and responsible AI practices.

This course teaches learners how to configure and operate an intelligent contact center using Microsoft contact center capabilities and integrated AI features. Learners focus on deploying and configuring contact center environments, including embedded and standalone modes, connecting data sources and third-party Contact Center as a Service (CCaaS) solutions, and enabling Copilot and agent capabilities that enhance the customer and agent experience. The course emphasizes understanding how channels, users, and security settings work together to support scalable and efficient customer engagement.

This course prepares learners to implement production-ready Copilot Studio agents and multi-agent solutions capable of sophisticated reasoning, workflow automation, and enterprise integration. Learners design agent architectures, configure advanced behaviors, integrate agents with external systems, and manage testing, deployment, monitoring, and application lifecycle management. These advanced solutions enable organizations to automate complex, cross-system workflows and deliver higher-value, domain-specific outcomes.

This course provides a comprehensive introduction to Microsoft 365, Copilot, and AI-powered agents. It introduces learners to the foundational concepts, core services, and administrative controls of Microsoft 365. It then builds upon this foundation by exploring how Copilot and agents can utilize AI to automate tasks, enhance collaboration, and personalize user experiences across the Microsoft 365 suite.

This course teaches developers how to create, monitor, and troubleshoot AI solutions on Microsoft Azure. Students will learn how to implement Azure compute and containerization patterns to host applications, build serverless APIs with Azure Functions, and integrate services using event-driven and message-based architectures such as Azure Service Bus and Event Grid. The course also covers working with Azure data services that support AI workloads, including designing and querying solutions with Cosmos DB for NoSQL, Azure Database for PostgreSQL with pgvector, and Azure Managed Redis for caching, streaming, and vector search. By the end of the course, developers will be able to connect services, orchestrate AI workflows, and build secure, scalable, and observable AI-driven applications on Azure.

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.