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Instructor-led training
Azure AI Cloud Development: AI-200 Preparation Training in London and Live Online

Azure AI Cloud Development: AI-200 Preparation

Develop secure Azure back-end components for AI applications. Prepare for AI-200 through practical work with containers, data services, messaging, application security and observability.

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Intermediate

Python programming experience and practical Azure knowledge, including storage, networking and application deployment.

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Course overview
Course dates
  • In Classroom
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  • 1 - 1 Training
  • Corporate Training
  • Onsite Training
Introduction
Develop secure Azure back-end components for AI applications. Prepare for AI-200 through practical work with containers, data services, messaging, application security and observability.


This instructor-led course combines clear explanations with guided exercises and practical scenarios. Work through examples relevant to the subject, review alternative approaches and practise checking your results rather than relying on a demonstration alone.
You will develop a structured approach to implementation, troubleshooting and documentation. The trainer can adapt examples to the agreed learning needs and available training environment. Confirm the course duration, software or lab requirements, delivery arrangements and fees with London IT Training before booking.
The course supports preparation for Exam AI-200: Developing AI Cloud Solutions on Azure. Training attendance does not award the credential. The awarding body sets separate examination, eligibility and experience requirements; confirm these and any exam fees before booking.
What the course covers
Flexible Ways to Learn

Study your way with flexible learning options designed to fit around your schedule.

Small Groups

With small groups of students, our instructors can work closely with each student

Flexible Class Schedules

Our class schedules are flexible on weekdays, weekend or evening to suit your schedule.

Experienced Instructors

Our instructors follow a modified and personalised approach to engage students during class

Hi-Tech lab Facilities

Lab arrangements vary by course. Confirm access and equipment requirements before booking.

Prerequisites
What you’ll gain

Apply container application delivery in a practical course exercise.

Apply data and vector retrieval in a practical course exercise.

Apply caching and application state in a practical course exercise.

Apply messaging and serverless integration in a practical course exercise.

Develop skills for your next step
Relevant career pathways
Technical Practitioner:

Apply the course skills to relevant technical tasks.

Technical Consultant:

Assess requirements and recommend practical implementation choices.

Syllabus

Course context and practical foundations
Review the course objectives and relevant concepts. Set up a suitable training environment, identify a realistic example and agree how to validate the results.

Build and version container images, select a hosting approach and manage application configuration and revisions.

Connect application code to Azure data services. Model sample records and evaluate vector retrieval and metadata filtering.

Choose cache and state patterns, define expiration and invalidation behaviour and test consistency expectations.

Implement asynchronous processing and serverless APIs. Handle retries, failed messages and duplicate events safely.

Use managed identities, protected secrets and appropriate permissions. Separate deployment configuration from application code.

Trace requests across components, query operational logs and diagnose connectivity, throughput and configuration failures.

Complete an integrated exercise using sample data or an isolated training environment. Test the result, document decisions and troubleshooting steps, and identify improvements and next learning objectives.

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FAQs

Who is this course for?
Develop secure Azure back-end components for AI applications. Prepare for AI-200 through practical work with containers, data services, messaging, application security and observability.

Python programming experience and practical Azure knowledge, including storage, networking and application deployment.

Container application delivery; Data and vector retrieval; Caching and application state; Messaging and serverless integration; Application identity and configuration; Observability and troubleshooting.

No. Check the awarding body’s current exam, experience and eligibility requirements. Exam booking and fees must be confirmed separately.

Contact London IT Training to discuss classroom, live online and corporate delivery arrangements.

Contact the training team for current duration, available dates, fees and software or lab requirements. Do not assume that licences, materials or examination fees are included.

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