Microsoft Azure: Cloud Solutions Mastery

This course provides a comprehensive introduction to artificial intelligence (AI) and its implementation using Microsoft Azure services, aligned with the AI-900 certification. Learners will explore core AI concepts including machine learning, responsible AI practices, and data processing fundamentals. Through hands-on examples and service walkthroughs, the course demystifies common AI workloads such as computer vision, natural language processing (NLP), and conversational AI. Participants will learn to analyze AI use cases, classify different types of machine learning models, and apply Azure-based tools like AutoML, ML Designer, Text Analytics, and Azure Bot Services to create no-code or low-code AI solutions. Emphasis is also placed on ethical considerations and responsible deployment of AI technologies. Designed for beginners, business users, and technical decision-makers, this course enables learners to understand, evaluate, and implement AI-driven applications using the Microsoft Azure ecosystem—empowering them to contribute meaningfully to intelligent solution development in modern organizations.

This hands-on course equips learners with the essential skills to design, develop, and deploy AI-based chatbots using Microsoft Azure Cognitive Services and Java. Tailored for intermediate-level participants, the course focuses on applying Azure’s QnA Maker to construct intelligent FAQ-driven bots and seamlessly integrate them into Java applications. Learners will begin by understanding core concepts of Azure’s cognitive architecture and then progress to configuring QnA services through a dedicated interface. They will build a chatbot back-end in Java, troubleshoot real-world integration issues, and validate the end-to-end deployment using Spring Tool Suite. Finally, learners will evaluate the impact of cloud-based services on operational costs and demonstrate how to perform responsible service cleanup in Azure. By the end of the course, learners will be able to: Design QnA knowledge bases using Azure Cognitive Services. Develop REST-enabled Java applications for chatbot integration. Diagnose and resolve common implementation issues during development. Execute and validate chatbot functionality through local and cloud-based environments. Optimize and manage Azure resources to ensure cost efficiency.

This hands-on course empowers learners to design, deploy, and manage scalable web applications using Microsoft Azure App Services and its associated cloud infrastructure. Through practical lessons and real-world scenarios, learners will explore the complete lifecycle of cloud application development—from provisioning resources and configuring databases to implementing secure APIs, logic workflows, and event-driven systems. The course begins with foundational concepts like deploying websites and configuring resource groups, followed by deep dives into service plans, remote connectivity, CORS policies, and content delivery optimization using Azure CDN. Learners will then develop skills to implement robust authentication, backup strategies, and workflow automation using Logic Apps. In the later modules, they will construct virtual machine environments, configure advanced networking elements such as subnets and route tables, and work with enterprise-grade messaging using Azure Service Bus and Azure Functions. Finally, the course wraps up with event-driven architecture patterns using Azure Event Grid. Throughout the course, learners will apply Bloom’s Taxonomy skills such as identifying, demonstrating, configuring, designing, implementing, and evaluating solutions using Azure tools. By the end of this course, learners will be able to: Deploy and manage Azure App Services for a variety of web applications Integrate services like SQL databases, CORS, and CDN for enhanced functionality and performance Secure applications with authentication and authorization models Automate business processes using Logic Apps and Azure Functions Construct cloud-native architectures with advanced networking and event-driven patterns This course is ideal for cloud developers, IT professionals, and solution architects who wish to apply, analyze, and evaluate real-time Azure scenarios in a production-ready environment.

This comprehensive, hands-on course is designed to empower learners to analyze, build, deploy, and optimize intelligent applications using Microsoft Azure Cognitive Services. Through a structured six-module framework, learners will explore a variety of AI-powered tools that mimic human cognition—including vision recognition, speech processing, language understanding, anomaly detection, personalization, and intelligent web search. Starting with foundational concepts and free-tier account setup, the course delves into real-world applications such as computer vision, face recognition, custom object detection, form and ink recognition, and natural language processing. Learners will gain proficiency in configuring and invoking REST APIs, training models, integrating services into applications, and visualizing insights. Advanced modules guide learners through building anomaly detection workflows, implementing decision-making logic via the Personalizer API, and enriching user experiences with Bing-powered web search capabilities. Each module is reinforced with hands-on exercises, quizzes, and application-driven learning objectives aligned with Bloom’s Taxonomy verbs such as "implement," "configure," "differentiate," "evaluate," and "design." By the end of the course, learners will be able to develop adaptable, AI-enhanced applications capable of processing visual data, interpreting language, detecting anomalies, and providing tailored user experiences in a cloud-first ecosystem.

This hands-on course enables learners to design, develop, and deploy cloud-based applications using Microsoft Azure’s Platform as a Service (PaaS) offerings. Through progressive modules, learners will identify core Azure services, configure Azure App Services, and implement secure identity management using Azure Active Directory. The course further explores how to integrate, test, and monitor automated background jobs with Azure WebJobs and connect applications to scalable storage systems including Azure SQL Database, Blob Storage, and Table Storage. Learners will actively apply connection strings, build real-world workflows for managing user data and media, and evaluate their deployments through portal logs and debugging tools. By the end of the course, participants will be able to construct end-to-end Azure application solutions, analyze WebJob outputs, and troubleshoot cloud-based deployments confidently using industry-standard practices.

This comprehensive course enables learners to design, implement, and deploy end-to-end machine learning solutions using Microsoft Azure Machine Learning. Through hands-on guidance, learners will configure development environments, build interactive experiments using Azure ML Designer, develop automation workflows via the SDK, and deploy models for real-time and batch inference using production-ready compute targets. The course is structured into four skill-building modules that introduce foundational cloud ML concepts, construct pipelines and SDK-based experiments, apply automation tools such as AutoML and HyperDrive, and publish trained models to production environments. Each module reinforces concepts through scenario-driven lessons that use Bloom’s Taxonomy to identify, configure, implement, analyze, and evaluate Azure ML workflows. By the end of this course, learners will be equipped to transition from experimentation to scalable deployment with full lifecycle awareness in Azure Machine Learning.

This comprehensive course equips learners with the practical skills and theoretical knowledge required to design, administer, secure, scale, and migrate relational database solutions in Microsoft Azure. Aligned with the Microsoft DP-300: Administering Relational Databases on Azure certification, this course prepares database professionals to manage cloud-native and hybrid data platform environments. Through hands-on demonstrations and scenario-based lessons, learners will: Identify core Azure database services and deployment models Evaluate business, functional, and scaling requirements Configure relational database environments using best practices Implement high availability, security, and performance tuning Apply advanced concepts like replicas, sharding, and synchronization Develop and execute robust migration and upgrade strategies using Azure-native tools By the end of the course, learners will be able to confidently manage relational databases in Azure and demonstrate competency in planning, optimizing, and transitioning database systems in enterprise cloud environments.

This course provides a foundational understanding of core data concepts and how they are implemented using Microsoft Azure data services. Through structured modules, learners will explore relational and non-relational data models, data storage solutions, database management systems, and the process of integrating, analyzing, and visualizing data using Azure’s modern cloud ecosystem. Participants will gain practical experience through demonstrations and quizzes that reinforce concepts such as data representation, normalization, structured query language (SQL), Azure SQL Database, Cosmos DB, Azure Data Factory, and Power BI. By the end of this course, learners will be prepared to identify appropriate data solutions for various business scenarios, describe capabilities of Azure data services, and confidently pursue the Microsoft DP-900 certification exam.

This comprehensive course offers a structured and hands-on journey through Microsoft Azure, tailored for aspiring cloud professionals and IT practitioners. Beginning with cloud computing fundamentals and an introduction to the Azure ecosystem, the course gradually builds proficiency in working with virtual machines, storage, networking, web applications, and advanced cloud configurations. Learners explore critical components such as Azure Virtual Networks, DNS, VPNs, storage scaling, and SharePoint deployment. Real-time use cases and capstone projects illustrate how to create scalable architectures, integrate desktop and recovery services, and perform cloud migration from on-premise systems. The course culminates with advanced Azure services like Machine Learning, HDInsight, BizTalk, and Traffic Manager, ensuring learners are well-prepared to design and manage enterprise-level cloud solutions. By the end of the course, participants will have gained not only theoretical knowledge but also practical expertise required for Azure certification paths and real-world implementation.

This comprehensive course empowers learners to construct, implement, monitor, and optimize data pipelines using Microsoft Azure Data Factory (ADF). Structured into four progressive modules, the course starts with foundational setup and connectivity, advancing to robust pipeline design, scheduling, debugging, and performance optimization using Azure Data Lake integration. Learners will configure source and destination datasets, execute copy activities, and deploy end-to-end workflows with precision. Through practical exercises, graded quizzes, and scenario-based tasks, learners will also diagnose failures, analyze pipeline behavior, and evaluate dataset and trigger configurations. By the end of the course, participants will be proficient in building dynamic, scalable, and production-ready data integration solutions using ADF. Designed for data professionals, engineers, and cloud practitioners, this course bridges theory with cloud-based implementation—helping learners transition from foundational concepts to enterprise-grade automation.

This hands-on course empowers learners to design, implement, and optimize data analytics solutions using Microsoft Azure Data Lake. Through a step-by-step, modular framework, participants will explore the fundamentals of scalable data storage, master U-SQL scripting for data transformation, and gain proficiency in job submission, performance tuning, and cost management using tools like Azure CLI, PowerShell, and Visual Studio. Learners will analyze real-world data scenarios, construct dynamic queries, deploy reusable views and functions, and evaluate job performance through diagnostics, heat maps, and vertex execution views. The course concludes with strategies to organize, secure, and manage data using both graphical and command-line tools, while also interpreting pricing models for efficient cost planning. Aligned with Bloom’s Taxonomy, this course encourages learners to: Understand the architecture and components of Azure Data Lake Apply U-SQL to perform data extraction, filtering, and aggregation Analyze job graphs and performance metrics for optimization Create reusable query logic using views, functions, and stored procedures Evaluate cost efficiency and scalability across access methods Manage data environments using automation and scripting interfaces

This comprehensive course offers a hands-on journey into the fundamentals and practical applications of Microsoft Azure, one of the leading cloud platforms in the industry. Designed for beginners and IT professionals aiming to build a strong foundation in cloud computing, the course starts with essential concepts such as the principles of cloud computing, service models, deployment strategies, and the Azure architecture. Learners will gain experience working with the Azure portal, explore the differences between ASM and ARM models, and understand Azure account structures, tools, and CLIs. The course then dives deep into provisioning and managing Azure Virtual Machines, understanding their pricing, architecture, and high availability configurations. Networking fundamentals such as virtual networks, subnets, NSGs, and load balancing are covered, followed by storage services including Blob, Disk, File, Table, and Queue storage. The course concludes with real-world scenarios in deploying scalable web applications using Azure App Services and WebJobs. Through engaging video content, demos, quizzes, and capstone-aligned lessons, learners will be equipped with the technical skills and architectural understanding to confidently operate in an Azure environment and lay the groundwork for more advanced certifications or cloud projects.

Unlock the full potential of cloud-native development with Microsoft Azure’s Platform as a Service (PaaS) in this hands-on course tailored for developers, IT professionals, and cloud enthusiasts. This course walks learners through the process of building, deploying, and scaling modern web and mobile applications using Azure’s powerful App Services, integrated development environments like Visual Studio, and robust backend solutions such as Azure Storage and Azure SQL Database. Through a combination of clear explanations and guided demos, learners will gain real-world expertise in provisioning cloud resources, automating deployments, managing backend services, and implementing secure, scalable architectures. Whether you're transitioning from traditional infrastructure or starting a new cloud-native project, this course equips you with the essential tools and best practices for leveraging Azure PaaS effectively. By the end of the course, learners will be capable of delivering full-featured applications on Azure’s managed platform with minimal operational overhead.

This practical course empowers developers and IT professionals to analyze, prepare, and execute the end-to-end migration of ASP.NET MVC applications and SQL databases to Microsoft Azure’s Platform-as-a-Service (PaaS). Through real-world scenarios and demonstrations, learners will evaluate application dependencies, configure Azure services, generate migration scripts, and deploy production-ready solutions using Azure Web Apps and Azure SQL Database. Each lesson guides learners to apply best practices, assess migration readiness, and validate post-deployment functionality. By the end of the course, participants will be able to confidently construct, modify, and optimize cloud-hosted .NET applications in an enterprise-grade environment. Ideal for intermediate .NET developers, cloud architects, and IT teams seeking a structured, actionable pathway to modernize legacy apps using Azure-native services.