Microsoft Azure AI Engineer Associate (AI-102) Training in Chennai-Edubrights

825 Ratings

Microsoft Azure AI Engineer Associate (AI-102) Course in Chennai

Advance your Artificial Intelligence career with Edubrights' Microsoft Azure AI Engineer Associate (AI-102) Course in Chennai. Designed for students, aspiring AI engineers, developers, cloud professionals, and working professionals, this training program helps you gain practical experience in designing, building, and deploying AI-powered solutions using Microsoft Azure through hands-on learning and real-world projects.

Learn how organizations leverage Azure AI services to develop intelligent applications, automate business processes, enhance customer experiences, and create scalable AI solutions. Through practical assignments, industry-focused case studies, and project-based training, you will gain the expertise needed to implement computer vision, natural language processing, conversational AI, and generative AI solutions in cloud environments.

Key Highlights:

✅ Real-Time Azure AI Projects and Industry-Based Case Studies

✅ Hands-On Training in Azure AI Services and Intelligent Application Development

✅ Computer Vision, Natural Language Processing, and Conversational AI Concepts

✅ Practical Exposure to Azure Cognitive Services and AI Solution Deployment

✅ Generative AI, AI Workloads, and Responsible AI Best Practices

✅ Microsoft AI-102 Certification Preparation and Exam Guidance

✅ Resume Building, Mock Interviews, and Placement Assistance

✅ Flexible Online, Classroom, and Weekend Training Options

Start your Azure AI journey with Edubrights and gain the practical skills, project experience, and cloud AI expertise needed to become a job-ready Azure AI Engineer and build intelligent solutions for modern business challenges.

Call Course Advisor

₹16000

₹20000

Enroll Now View Syllabus

Case Studies and Projects

Hours of Training

20+

Placement Assurance

100%

Expert Support

Yes

Support & Access

Lifetime

Certification

Yes

Skill Level

All

Language

All

Course Objectives

1.What exactly Microsoft Azure AI Engineer Associate (AI-102) training cover?

Microsoft Azure AI Engineer (AI-102) training covers designing, building, managing, and deploying AI solutions using Azure Cognitive Services, Azure OpenAI, Cognitive Search, and the Bot Framework. You’ll gain hands-on skills in computer vision, natural language processing, conversational AI, and generative AI—including planning, securing, and optimizing end-to-end AI systems

2. What are the main objectives of the Microsoft Azure AI Engineer Associate (AI-102) course for your development skills?

Enable you to develop, operationalize, and monitor robust AI solutions on Azure.
Equip you to integrate computer vision, NLP, conversational agents, and generative AI into real business scenarios.
Teach best practices for secure, responsible AI implementation and optimizing cloud-based AI services

Deploy Advanced NLP and Mining Pipelines

Create hybrid (keyword and vector) search indexes and deep language understanding models using Azure AI Language and AI Search.

Implement Enterprise AI Safety & Governance

Architect secure multi-tenant AI workloads featuring virtual network isolation, key management, content filters, and PII safeguards.

Popular Techniques Covered in This Course

1.Azure Cognitive Services (Vision, Language, Speech)

2.Generative AI and prompt engineering (Azure OpenAI)

3.Azure AI Search and document intelligence

4.Building and deploying chatbots

5.NLP and computer vision techniques

6.Responsible AI and compliance

7.Security and access management for AI workloads

8.Real-world data integration and transformation

9.Monitoring, logging, and cost optimization

10.REST APIs, SDKs, and cloud application design

Get Hands-on Knowledge about Real-Time Projects

Project 1

1.Conversational AI Chatbot:

Design and deploy a multi-turn chatbot solution integrating Azure Bot Service with LUIS for intent recognition and Azure Cognitive Services for Q&A.

Project 2

2.Intelligent Document Processing:

Create a pipeline using Azure Document Intelligence and Azure AI Search to extract, analyze, and search data from a set of scanned business documents.

Project 3

3. Multi-Lingual Customer Feedback Sentiment Engine

Construct an active customer support sorting mechanism that reads incoming product reviews in real-time. By connecting Azure AI Language APIs, your backend script will auto-detect original languages, scrub PII data, and flag negative-sentiment accounts for priority routing.

Project 4

4. Smart Warehouse Spatial Awareness Tracker

Project 5

5. Multi-Step Support Agent and CRM Integrator

Program a production-ready autonomous agent capable of resolving client tasks without human intervention. Utilizing Semantic Kernel SDK patterns, your agent will interpret user intent, pull historical context from databases, and execute live API calls into a CRM system.

Key Features

Edubrights offers Microsoft Azure AI Engineer Associate (AI-102) Training in virtual mode with expert trainers. Here are the key features,

40 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Curriculum

Module 1: Planning and Managing Azure AI Solutions

Designing end-to-end Azure AI architectures
Security, compliance, and cost management for AI services
Monitoring and troubleshooting deployed AI solutions

Module 2: Implementing Computer Vision Solutions

Image classification, object detection, and OCR with Azure AI Vision
Video analysis with Azure Video Indexer
Custom model training for vision tasks

Module 3: Implementing Natural Language Processing (NLP) Solutions

Text analytics: sentiment, key phrases, entity extraction
Language modeling, translation, and summarization
Custom NLP solutions with Azure AI Language

Module 4: Building Conversational AI Applications

Designing and developing chatbots with Azure Bot Service
Integrating bots with LUIS for language understanding
Conversational design, deployment, and monitoring

Module 5: Implementing Knowledge Mining Solutions

Creating intelligent search with Azure AI Search
Document extraction and knowledge mining with Document Intelligence
Vector and semantic search, cognitive skills integration

Module 6: Developing Generative AI Solutions

Understanding and using Azure OpenAI models (GPT, DALL-E)
Prompt engineering and RAG (Retrieval Augmented Generation)
Responsible AI practices for generative content

Module 7: Capstone Project

End-to-end solution incorporating vision, language, and conversational AI on Azure

Receive Training From Our Skilled and Effective Trainers

Experience in the Industry Gain knowledge from experts with practical Microsoft Azure AI Engineer Associate (AI-102) project experience in a variety of sectors.

Backgrounds at the Top Prominent corporations such as hcl, tcs , accenture and cognizant employ trainers.

Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.

Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.

Up-to-Date Knowledge Trainers stay current with the latest tools, techniques and best practices.

Succeed Our Resourceful Certification

Our institution’s Microsoft Azure AI Engineer (AI-102) certification proves your ability to design, build, and operationalize advanced AI solutions using Azure Cognitive Services, OpenAI, and Bot Framework. Gain hands-on expertise in generative AI, vision, language, and intelligent search for real-world business needs. This globally recognized credential opens doors to in-demand careers in AI and cloud development

Course FAQs

Q1: What is the AI-102 certification?

It validates your skills in designing and implementing Microsoft Azure AI solutions—including generative AI, vision, NLP, bots, and more

Q2: What services are covered in AI-102?

Azure Cognitive Services (Vision, Language, Speech), Azure OpenAI, Cognitive Search, and Bot Framework

Q3: Does it include generative AI?

Yes, working with GPT, DALL-E, and prompt engineering are an important part of the syllabus

Q4: Is prior AI or data science experience required?

Experience developing cloud apps is recommended, but deep data science expertise is not required

Q5: What programming languages can I use?

You can use Python, C#, JavaScript, or any language supported by Azure SDKs

Q6: Do I need to know about responsible AI?

Yes, the exam covers responsible AI principles (fairness, privacy, transparency) and implementation

Q7: Are hands-on labs included in training?

Yes, labs typically involve real scenarios—like building bots, vision, or document intelligence solutions

Q8: How is the exam delivered?

Multiple-choice, scenario-based, and task simulation questions, taken online or at test centers

Q9: Is AI-102 recognized by employers?

Yes—AI-102 is globally recognized and highly valued for AI/cloud tech roles

Q10: Can I integrate Azure AI with other Microsoft services?

Absolutely—AI-102 covers integration with storage, analytics, web, and business solutions

Q11: What is the main difference between Azure Cognitive Services and Azure OpenAI?

Azure Cognitive Services provides pre-built, task-specific models for traditional vision, speech, and translation workflows. Azure OpenAI provides access to generalized foundational models (like GPT-4) that handle open-ended text creation, code development, and reasoning tasks.

Q12: Will I learn how to deploy AI models inside isolated Docker containers?

Yes. Enterprise architectures often require on-premises edge computing or strict network isolations. You will learn how to pull Azure AI Docker container images, configure localized endpoint keys, and run vision or text APIs completely inside containers.

Q13: Does the curriculum cover the implementation of Responsible AI guidelines?

Absolutely. Responsible AI is heavily evaluated on the exam. You will study how to customize content safety filters, implement blocklists for harmful prompts, track model behavior for fairness, and safeguard private user data.