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This course teaches developers how to create, monitor, and troubleshoot AI solutions on Microsoft Azure.
Prepares for Exam:
Microsoft Azure AI Cloud Developer AI-200
Prepares for Certification:
Microsoft Certified: Azure AI Cloud Developer Associate Certification
Attend this and 60+ other Microsoft courses for FREE with Unlimited Microsoft Training
Overview
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.
Instructor-led training
Practice test
Pre-reading
Personal Learning Path
Certification Guarantee
Email, chat and phone support
Who is this course for?
This course is designed for developers who build backend and AI driven applications on Azure and need practical skills in containerized compute, data services for AI, event driven workflows, and application security and monitoring.
Curriculum
Preparation
At Readynez, we provide many resources and have experienced experts in the field. That is why we are also very successful with many satisfied customers. You can therefore safely take your course with us. While there are no strict entry requirements, certain foundational knowledge may enhance your learning experience. Any recommended prerequisites specific to this course are detailed below..
Programming experience with languages such as Python, JavaScript, or C#.
Basic understanding of Azure services and cloud computing concepts.
Basic understanding of message queuing patterns and when to use them for decoupling services.
Understanding of machine learning concepts including embeddings and similarity search.
Knowledge of caching concepts and data structures.
Familiarity with command-line tools including Azure CLI.
Familiarity with containerization and Kubernetes fundamentals.
Familiarity with JSON document structures.
Familiarity with relational databases and SQL fundamentals.
Familiarity with AI embeddings and vector similarity concepts.
Familiarity with distributed systems concepts and event-driven architectures.
Familiarity with REST APIs and asynchronous messaging patterns.
Familiarity with distributed application architectures.
Access to Azure Kubernetes Service and related tools for practical exercises.
Access to Azure Managed Redis and related tools for hands-on practice.
Meet some of the Readynez Instructors you can meet on your course. They are experts, passionate about what they do, and dedicated to give back to their industry, their field, and those who want to learn, explore, and advance in their careers.
With a long-standing reputation as a Microsoft MVP and MCT, Tiago Costa delivers LIVE training that blends expert knowledge with real-world application. His courses help professionals build hands-on cloud skills and prepare effectively for Microsoft certifications.
Wilson Tsui Sie Min, an experienced Azure and cloud instructor delivers LIVE IT training and certification courses at Readynez. With nearly two decades of global training and infrastructure experience, Wilson helps IT professionals prepare for Azure exams, strengthen cloud skills, and apply practical knowledge through expert-led training.
FAQ
The Microsoft AI-200 certification validates your ability to develop, deploy, integrate, monitor, and secure AI-powered cloud applications on Microsoft Azure.
This course is designed for developers, cloud engineers, AI engineers, backend developers, and IT professionals who want to build AI applications using Microsoft Azure.
Learners should have basic Azure knowledge, software development experience, and familiarity with APIs, cloud computing, and programming concepts.
Yes. The course includes practical labs, real-world scenarios, AI integrations, deployment exercises, and cloud-native development projects.
The course covers Azure AI Services, Azure OpenAI, Azure Functions, Azure Kubernetes Service (AKS), Cosmos DB, Event Grid, Service Bus, Azure PostgreSQL, and more.
AI-200 is an intermediate-level course. Basic Azure and programming experience is recommended before enrolling.
Examples may include Python, C#, JavaScript, and REST APIs depending on the learning modules and labs.
Yes. Learners receive a course completion certificate, and the training prepares candidates for the Microsoft AI-200 certification exam.
AI-200 certification can help professionals pursue roles such as Azure AI Developer, AI Engineer, Cloud Developer, AI Solutions Architect, Backend AI Developer, and Cloud Application Engineer.
Yes. The course includes Azure OpenAI concepts, integrations, and AI application development workflows.
Yes. Learners explore modern AI development topics including Generative AI applications, Retrieval-Augmented Generation (RAG), embeddings, vector search, and AI orchestration patterns.
Absolutely. The course focuses on enterprise-grade AI cloud architecture, observability, scalability, deployment, security, and operational best practices.
Reviews
Readynez is the best training provider I've used for many years. Their customer service is first class, prices are very competitive and instruction excellent.
Easy to attend over Teams and an excellent instructor gave me great value for the time I invested.
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