---
url: "https://xcademia.com/courses/azure-ai-engineer-training"
title: " Azure AI Engineer Training"
description: " Learn Azure AI with this 4-day AI-102 training. Build NLP, vision, and generative AI apps using Cognitive Services and Azure OpenAI."
publishedAt: "2026-03-20T12:03:54.53059+00:00"
updatedAt: "2026-03-30T22:50:53.7265+00:00"
type: course
code: "CLD-0099"
level: Professional
duration_days: "4"
track: Azure Tracks
category: "Cloud & DevOps"
credential_tier: tier1
price_gbp: "1999"
---

#  Azure AI Engineer Training

> Build intelligent applications using Azure AI services aligned with AI-102 certification objectives. Learn through hands-on labs covering Cognitive Services, Azure OpenAI, NLP, vision, and bots.

## Overview

This Azure AI Engineer Training programme is designed for developers and IT professionals looking to build AI-powered applications using Microsoft Azure. Aligned with AI-102 certification objectives, the course provides a practical and structured approach to designing and deploying intelligent solutions.

Through mentor-led sessions and hands-on labs, learners will work with Azure Cognitive Services, Azure OpenAI, and AI workloads such as natural language processing, computer vision, and conversational AI. The course focuses on integrating AI into real-world applications, including chatbots, automation, and intelligent data processing systems.

By the end of this programme, participants will be able to design, build, and deploy scalable AI solutions on Azure. This course prepares learners for AI engineering roles and supports progression into advanced AI, machine learning, and cloud solution architecture pathways.

## Prerequisites

- Basic programming knowledge (Python or similar)
- Understanding of cloud computing concepts
- Familiarity with APIs and data handling

## What you will learn

- Design AI-powered cloud applications
- Implement NLP and conversational AI solutions
- Analyse image and document data
- Evaluate generative AI use cases
- Integrate AI services into applications
- Manage deployment, security, and performance

## Skills you will gain

- Azure Cognitive Services usage
- Azure OpenAI integration
- NLP and chatbot development
- Computer vision implementation
- AI application deployment
- AI security and governance

## Career progression

- AI Engineer
- Cloud AI Developer
- Machine Learning Engineer
- Software Engineer – AI
- Data Engineer

## Curriculum

1. **Module 1**
2. **Module 2**
3. **Module 3**
4. **Module 4**

## Exam & certification

This programme is aligned with the official exam objectives. Exam registration and certification are managed directly by the awarding body.

## Delivery options

- **Live Online** — Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
- **Onsite Training** — We come to you. Training delivered at your workplace for teams of 6 or more.
- **Venue-Based** — Classroom training at a professional venue. Ideal for focused, immersive learning.
- **Blended** — Combine online and in-person learning for maximum flexibility and impact.

## Frequently asked questions

**Is this course aligned with AI-102 certification?**

Yes, it is aligned with Microsoft AI-102 certification objectives.



**Do I need programming experience?**

Basic programming knowledge is recommended, especially in Python.



**Are hands-on labs included?**

Yes, extensive labs are included for real-world AI scenarios.



**Does this course need an exam?**

No, the exam is optional and can be taken separately.



**What roles can I pursue after this course?**

Roles include AI Engineer, Machine Learning Engineer, and Cloud AI Developer.

## Course at a glance

| Field | Value |
| --- | --- |
| Code | CLD-0099 |
| Duration | 4 days |
| Level | Professional |
| Track | Azure Tracks |
| Category | Cloud & DevOps |
| Credential tier | tier1 |
| Price (GBP) | £1999 |

---

## About this content

This Markdown course profile is the citation-grade twin of [ Azure AI Engineer Training](https://xcademia.com/courses/azure-ai-engineer-training). It is published by **Xcademia** (UK Companies House 12322710) and is available for AI search engines and large language models to index, summarise, and cite.

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