​​"Discover Microsoft AI for Leaders in Healthcare"​​ is a ​​3-hour 21-minute strategic training program​​ designed for healthcare executives, clinical leaders, and innovation managers. This course equips healthcare professionals with actionable frameworks to integrate AI into clinical workflows, administrative processes, and patient care systems. Participants will explore Microsoft’s AI ecosystem—including ​​Azure AI Services​​, ​​Microsoft Power Platform​​, and ​​Copilot Studio​​—to address challenges like workforce burnout, diagnostic accuracy, and interoperability. The curriculum combines foundational AI concepts with healthcare-specific use cases, such as AI-driven medical imaging analysis, clinical trial matching, and automated documentation tools like DAX Copilot. Emphasizing ​​responsible AI governance​​, the training aligns with Microsoft’s commitment to ethical AI adoption in healthcare, demonstrated through collaborations with institutions like Stanford Medicine and Providence Health.

"Implement AI Models with Microsoft Power Platform AI Builder"​​ is a ​​3-hour 12-minute hands-on course​​ designed for business users and developers seeking to automate workflows using no-code AI solutions. The curriculum focuses on ​​document processing automation​​, ​​text recognition​​, and ​​predictive modeling​​ through AI Builder's prebuilt and customizable tools. Participants will learn to extract data from invoices, analyze unstructured text, and deploy AI-driven approval systems in Power Automate. Real-world scenarios, like building an invoice-to-email approval pipeline, bridge theory with practice, while integration guides for Power Apps demonstrate how to embed AI controls (e.g., sentiment analysis widgets) into business applications.

This learning path, End-to-End Machine Learning Operations (MLOps) with Azure Machine Learning, teaches you to apply DevOps principles to machine learning projects. Over six modules and 3.5 hours, you'll master automation, CI/CD pipelines, and source control using Azure Machine Learning and GitHub Actions. Designed for Python/R developers with ML experience, the course guides you from model experimentation to production deployment, emphasizing scalable, repeatable workflows.

This learning path, Discover Microsoft AI for Leaders in Retail, equips retail business leaders with the knowledge to adopt AI strategically and responsibly. Over five modules and 3.5 hours, explore Microsoft's AI tools, frameworks for creating business value, responsible AI governance, scaling strategies, and retail-specific use cases. Designed for decision-makers, the course combines foundational AI concepts, cultural readiness, and practical insights from real-world success stories like CarMax, empowering leaders to drive innovation and efficiency in retail operations.

This learning path, Implement Generative AI Engineering with Azure Databricks, equips you with advanced skills to design, fine-tune, and deploy generative AI systems using Azure Databricks. Over seven modules and nearly seven hours, you'll explore Large Language Models (LLMs), implement Retrieval Augmented Generation (RAG), apply multi-stage reasoning, and integrate responsible AI principles. Leveraging Apache Spark's scalability and Azure Databricks' collaborative tools, the course focuses on practical engineering workflows—from model evaluation to lifecycle management (LLMOps)—for building enterprise-grade AI solutions.

"Introduction to Artificial Intelligence for Trainers" is a ​​2-hour 36-minute course​​ designed to equip educators and trainers with foundational AI knowledge and practical strategies for enhancing learning experiences. Through four modules, you'll explore AI principles, machine learning basics, and real-world applications in education. Learn to integrate AI tools like ​​Microsoft Speaker Coach​​ and ​​Sway​​ into training programs, evaluate AI efficacy, and adapt teaching methods to leverage AI's potential. Ideal for non-technical professionals, the course bridges theory with hands-on activities to make AI accessible and actionable in educational settings.

This ​​1-hour 57-minute course​​, Integrate Azure Cosmos DB for NoSQL with Azure Services, teaches developers to connect Azure Cosmos DB's NoSQL API with critical Azure tools like ​​Azure Functions​​ and ​​Azure Cognitive Search​​. Designed for intermediate developers, it focuses on real-time data processing using the ​​change feed​​ feature, serverless automation with Functions bindings, and enabling intelligent search capabilities. Learn to build event-driven architectures, automate data workflows, and create full-text search indexes—all while leveraging Cosmos DB's scalability and low-latency strengths.

This ​​1-hour 44-minute course​​, Build a Foundation to Extend Microsoft 365 Copilot and AI Agents, empowers developers and IT professionals to customize and deploy AI-driven solutions using Microsoft's ecosystem. Through four modules, you'll explore tools like ​​Copilot Studio​​, ​​Azure AI Foundry​​, and the ​​Microsoft 365 Agents Toolkit​​ to build, extend, and integrate AI agents. Learn to enhance productivity by embedding custom logic into Microsoft 365 Copilot, create declarative agents, and scale enterprise-grade solutions—all while aligning with business goals and technical requirements.

This ​​8.5-hour course​​, Implement a Machine Learning Solution with Azure Databricks, equips data scientists and engineers to build, optimize, and deploy scalable ML workflows using Azure Databricks. Designed for professionals familiar with machine learning, the course covers end-to-end processes—from data preparation with Apache Spark to production deployment. Dive into hyperparameter tuning with Hyperopt, automate model development with AutoML, manage experiments with MLflow, and train deep learning models for advanced AI tasks. Learn to streamline collaboration and operationalize ML pipelines in a unified cloud environment.

This ​​3.5-hour course​​, Execute Queries and Build a Generative AI Application with Azure Cosmos DB, teaches developers to harness the power of Azure Cosmos DB for NoSQL through advanced querying and AI integration. Learn to write SQL queries (using SDKs for .NET, Python, and Node.js) and optimize data retrieval with projections, subqueries, and pagination. Then, dive into building generative AI applications using ​​Azure OpenAI embeddings​​, ​​vector search​​, and ​​LangChain orchestration​​ for Retrieval-Augmented Generation (RAG). Perfect for developers aiming to combine scalable NoSQL data management with cutting-edge AI solutions.