Azure AI Engineer Course in Hyderabad
Build AI applications and agents with Azure AI services and Azure OpenAI
The Azure AI Engineer course teaches you to design and build AI solutions on Microsoft Azure. You begin with Python, REST APIs and responsible AI principles, then use Azure AI services for vision, speech, language and document intelligence, build search-driven applications with Azure AI Search, and create generative AI applications with Azure OpenAI models in Microsoft Foundry. Later modules cover retrieval-augmented generation, prompt design, evaluation, content safety, building and orchestrating agents, and deploying and monitoring AI workloads securely with managed identities, Key Vault and Azure Monitor. Microsoft retired the AI-102 Azure AI Engineer Associate exam on 30 June 2026, and a newer exam called AI-103 was reported as its replacement, so this course is skill-focused and a counsellor will confirm current certification options. It suits developers, data professionals and graduates with basic Python who want AI engineering roles. Every module has a hands-on lab and the course ends with a capstone assistant. Classes run in Ameerpet, Hyderabad, and in live online batches.
Syllabus
AI Foundations & Responsible AI
- •AI workloads: vision, language, speech, search and generative AI
- •Python and REST API refresher; using the Azure SDKs
- •Microsoft responsible AI principles and risk awareness
- •Lab: Set up an Azure subscription, resource group and AI resources
- •Outcome: Plan an AI solution and choose the right Azure service
Azure AI Services Setup & Security
- •Creating and consuming Azure AI services resources
- •Authentication with keys, Microsoft Entra ID and managed identities
- •Key Vault, private endpoints and cost monitoring
- •Lab: Call an AI service securely without hard-coded keys
- •Outcome: Provision and secure AI resources
Computer Vision Solutions
- •Image analysis, captioning, tagging and object detection
- •Optical character recognition and reading text from images
- •Custom vision and face-detection concepts; video analysis overview
- •Lab: Build an image-captioning and text-extraction app
- •Outcome: Add vision features to an application
Natural Language Processing Solutions
- •Azure AI Language: sentiment, key phrases, entities and summarisation
- •Question answering and custom classification
- •Azure AI Translator
- •Lab: Build a support-ticket classifier and summariser
- •Outcome: Extract meaning from text in applications
Speech & Conversational Interfaces
- •Speech to text, text to speech and speech translation
- •Custom speech and voice considerations
- •Conversational language understanding and bot concepts
- •Lab: Build a voice-enabled helper that transcribes and replies
- •Outcome: Create speech-enabled experiences
Document Intelligence & Content Understanding
- •Azure AI Document Intelligence: layout, prebuilt and custom models
- •Extracting fields from invoices, receipts and forms
- •Content Understanding concepts for multimodal data
- •Lab: Extract invoice data into a database
- •Outcome: Automate document processing
Azure AI Search & Knowledge Mining
- •Search service, indexes, indexers and data sources
- •AI enrichment skillsets and the knowledge store
- •Full-text, semantic, vector and hybrid search
- •Lab: Index a PDF collection and run hybrid queries
- •Outcome: Build a searchable knowledge base
Generative AI with Azure OpenAI & Foundry
- •Microsoft Foundry projects, model catalogue and deployments
- •Chat completions, system prompts, few-shot examples and structured output
- •Token limits, quotas, cost and parameters
- •Lab: Build a chat application with conversation memory
- •Outcome: Build reliable prompts and chat applications
Retrieval-Augmented Generation
- •RAG architecture and chunking strategies
- •Connecting Azure OpenAI to Azure AI Search; citations
- •Evaluating groundedness and relevance
- •Lab: Build a grounded question-answering assistant over company documents
- •Outcome: Deliver answers based on your own data
Agents & Orchestration
- •Agent concepts: instructions, tools, memory and threads
- •Function calling and tool integration; Model Context Protocol overview
- •Multi-step workflows and human approval points
- •Lab: Build an agent that calls a business API
- •Outcome: Create agents that act within guardrails
Safety, Evaluation & Monitoring
- •Azure AI Content Safety, prompt shields and filters
- •Evaluation of quality, safety and groundedness; test datasets
- •Tracing, logging and monitoring with Azure Monitor and Application Insights
- •Lab: Run an evaluation and add content filters to the assistant
- •Outcome: Test and monitor AI applications before and after release
Deployment, Containers & Cost
- •Deploying AI applications to Azure App Service and Container Apps
- •Using containers for AI services where supported; CI/CD basics
- •Quotas, throttling, caching and cost optimisation
- •Lab: Deploy the assistant and set budget alerts
- •Outcome: Operate an AI workload within cost and reliability goals
Capstone & Certification Guidance
- •Capstone: multimodal assistant combining search, documents and an agent
- •Presentation, portfolio write-up and interview practice
- •Current Microsoft AI certification options and exam objectives
- •Outcome: A deployed AI project and an informed certification plan
Tools Covered
Projects Included
- Smart Document Processor: Extract invoice fields with Document Intelligence and store them in a database; deliverable is a working pipeline and accuracy notes.
- Support-Ticket Analyser: Classify, summarise and translate tickets using Azure AI Language; deliverable is an API with sample results.
- Enterprise Knowledge Assistant: Build a RAG assistant with Azure AI Search and Azure OpenAI with citations; deliverable is a web demo and evaluation report.
- Safe Agent for Order Queries: Create an agent with function calling and content safety filters; deliverable is a tested agent and safety test log.
- Capstone AI Assistant: Combine search, speech and an agent in a deployed application with monitoring; deliverable is a GitHub repository and architecture diagram.
Start Your Journey Today
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Call: +91 9908099980Prerequisites & Eligibility
Understand the foundation and skills needed to succeed in the Azure AI Engineer course.
Course Prerequisites
- Any graduate is eligible for enrollment across all program tracks
- Dedication to work on real-time scenario projects and live client project implementations
- Willingness to engage in aptitude, soft skills and interview readiness sessions
- Commitment to complete full-day training or intensive/internship program schedules
Why Choose GloryTecks
Build practical capabilities through structured learning, expert mentors and hands-on projects.
5+ Years of Excellence
Established training institute in Hyderabad with a proven track record of producing industry-ready professionals.
Expert Faculty
Learn from trainers with real-world industry experience, who teach the way the work is actually done.
Placement Assistance
A dedicated placement team with tie-ups across hiring companies. We support you until you get hired.
Comprehensive Curriculum
Updated syllabus covering the latest technologies and industry best practices, with hands-on projects.
Career Growth Focus
Not just training, but complete career transformation with soft skills and interview preparation.
Online & Classroom
Attend live online batches or classroom training at our Ameerpet centre, whichever suits you.
Flexible Batches
Weekday, weekend and online batch timings to suit working professionals, students and freshers.
Real-time Projects
Work on real-time scenario projects so you finish with practical experience to show employers.
We provide placement support with direct access to hiring companies, along with comprehensive training that helps freshers become job-ready professionals.
Certification
Explore certification and practical learning opportunities with a focus on Azure AI Engineer.
Certificate of Completion
Azure AI Engineer
This certifies that
[Your Name]
has successfully completed the
Azure AI Engineer
Training Program
GloryTecks
Ameerpet, Hyderabad
Certificate ID
GT-YYYY-XXXX
Certificate Includes
- Course completion certificate from GloryTecks
- Project completion certificates
- Internship completion certificate for eligible internship programs
- Digital certificate with a unique verification ID
- Shareable on LinkedIn and other professional platforms
- Valid proof of skill acquisition for employers
- Includes the detailed syllabus covered
Industry Focus
A certificate built around the tools and skills employers ask for, adding credibility to your resume.
Skill Validation
Proves your expertise in the course and the technologies you worked with.
Career Advancement
Strengthens your profile when you apply for jobs and negotiate your salary.
Digital & Physical
Get a digital certificate for online sharing and a physical copy for framing.
Course Certificate
Upon successful completion of the training program
Project Certificate
For major projects completed during training
Course Features & Highlights
Build a strong foundation through a structured Azure AI Engineer course with practical learning and hands-on exposure.
Live Projects
Work on real-world projects from day one with industry use cases.
Expert Trainers
Learn from industry professionals with real-world experience.
Placement Support
Dedicated placement team with assistance until you get hired.
Industry Certification
Get certified and boost your resume with recognized credentials.
LMS Access
Access to learning materials and recorded sessions.
Mock Interviews
Weekly mock interviews to prepare you for real job scenarios.
Resume Building
Professional resume preparation and LinkedIn profile optimization.
Additional Benefits
- Flexible Payment Plans
- 6-12 Months LMS Access
- Doubt Clearing Sessions
- 24/7 Learning Support
Frequently asked questions
What does the Azure AI Engineer course syllabus cover?
What happened to the Azure AI Engineer Associate (AI-102) certification?
Do I need machine learning knowledge to join?
Will I use OpenAI models?
Is this the same as the Generative AI course?
Will I need to pay for Azure services?
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What jobs can I apply for after this course?
How long is the Azure AI Engineer course at GloryTecks, and how many hours a week?
Is the Azure AI Engineer course available as live online training?
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Best Azure AI Engineer Training in
Ameerpet, Hyderabad
Located at Ameerpet — Hyderabad’s IT training hub. Easily accessible from all areas of Hyderabad. Just 2 minutes walk from Ameerpet Metro Station.
Placement Support
Career support covers resume and LinkedIn preparation, mock interviews and a portfolio of 5 course projects. Roles that use these skills include AI Engineer, Generative AI Developer, Azure Developer (AI), Conversational AI Developer; support is guidance with the job search, not a guarantee of a job.