jacintainfotech@gmail.com

  • 9100270734 | 8309515643
Facebook Youtube Instagram Linkedin
Menu

Azure Ai Engineer Course

Azure Ai Engineer Certification Training is designed to equip learners with the knowledge and practical skills needed to design, build, manage, and deploy AI solutions using Microsoft Azure. This course focuses on integrating Azure Cognitive Services, Azure Machine Learning, and conversational AI to create intelligent, scalable, and secure applications.

Whether you’re preparing for the Microsoft Certified: Azure AI Engineer Associate (AI-102) exam or looking to enhance your career in the AI domain, this course provides hands-on experience through real-world projects and cloud-based labs.

Azure Ai Engineer Certification Training – Course Overview

Azure Ai Engineer Course is a comprehensive training program tailored for professionals aiming to master the design and deployment of AI-powered solutions using Microsoft Azure. The course focuses on real-world application of Azure Cognitive Services, Machine Learning, and Conversational AI to solve business problems. Aligned with the Microsoft AI-102 certification, this course blends theory, hands-on labs, and projects to make you job-ready in the growing field of AI on the cloud.

Azure Ai Engineer Certification Training

Key Highlights 

  • 🎯 Certification-Oriented: Aligned with Microsoft Certified: Azure AI Engineer Associate (AI-102)

  • 🧠 Hands-on Experience: Practical labs on Azure Cognitive Services, LUIS, Bot Framework, and Azure ML

  • 🧑‍💻 Live Projects: Work on AI solutions like chatbots, image classifiers, and sentiment analyzers

  • ☁️ Cloud-Native Learning: Gain expertise in deploying and managing AI models on Azure cloud

  • 📚 Expert-Led Training: Learn from certified Azure professionals with real-world experience

  • 📈 Career-Focused: Resume building, mock interviews, and job placement assistance included

  • 🕒 Flexible Format: Online live classes, weekend batches, and recorded sessions available

  • 🎓 Certification Support: Full guidance for Microsoft AI-102 exam preparation

  • 🔒 Secure & Responsible AI: Learn AI governance, privacy, and ethical deployment practices

  • 🔁 Lifetime Access: Revisit course material and recorded sessions anytime

What Will You Learn in Azure Ai Engineer Course?

Azure Ai Engineer Certification Training equips you with the practical skills and technical knowledge needed to design, build, and deploy intelligent AI solutions using Microsoft Azure’s powerful tools and services. Here’s what you’ll learn:

  • Fundamentals of Artificial Intelligence
    Understand AI concepts, machine learning basics, and responsible AI practices.
  • Azure Cognitive Services
    Work with APIs for vision, speech, language, and decision-making capabilities including:
    Face and Emotion Recognition, Text Analytics, Language Detection, Speech-to-Text, Text-to-Speech, and Translation.
  • Natural Language Processing (NLP)
    Use Language Understanding (LUIS) to process and interpret human language inputs effectively.
  • Conversational AI with Azure Bot Services
    Design, build, and deploy chatbots using the Microsoft Bot Framework integrated with LUIS.
  • Azure Machine Learning (Azure ML)
    Create, train, evaluate, and deploy machine learning models using Azure ML Studio and SDK.
  • Computer Vision & Custom Vision
    Implement object detection, image classification, OCR, and build your own custom vision models.
  • AI Model Deployment & Integration
    Deploy AI models as web services, integrate them into apps using REST APIs, and secure endpoints.
  • Real-World Projects
    Apply your skills to real use cases like virtual agents, image recognition tools, and language translation systems.
  • AI-102 Certification Preparation
    Learn all core modules and topics required to pass the Microsoft AI-102: Designing and Implementing an Azure AI Solution certification exam.

Azure Ai Engineer Certification Training-Course Curriculum

Module 1: Introduction to AI and Azure AI Services

  • Overview of Artificial Intelligence and Machine Learning

  • Introduction to Microsoft Azure AI ecosystem

  • Responsible AI principles and governance

  • Overview of AI-102 certification objectives

  • Overview of Cognitive Services

  • Authentication and authorization for cognitive services

  • Using Computer Vision API for image analysis and OCR

  • Working with Face API and Custom Vision

  • Deploying and training models using Custom Vision Portal

  • Text Analytics API for key phrase extraction and sentiment analysis

  • Language Detection and Translation using Translator API

  • Entity recognition and PII detection

  • Introduction to Azure OpenAI and Language models

  • Introduction to Azure Bot Service and Bot Framework SDK

  • Creating intelligent bots using QnA Maker and LUIS

  • Integrating LUIS for intent recognition and entity extraction

  • Deploying bots to Microsoft Teams, Web Chat, and other channels

  • Introduction to Azure Machine Learning Studio

  • Creating and managing datasets and compute environments

  • Training, evaluating, and tuning machine learning models

  • Automated ML and responsible AI model deployment

  • Monitoring and retraining models in production

  • Securing Cognitive Services with keys and identity access

  • Logging, monitoring, and diagnostics for AI services

  • Rate limiting and scaling AI services

  • Cost optimization strategies for AI workloads

  • Project 1: Build a Smart Chatbot using Bot Framework and LUIS

  • Project 2: Image Classification using Custom Vision

  • Project 3: Sentiment Analysis with Text Analytics API

  • Project 4: AI Model Deployment using Azure ML

  • Practice questions and mock exams

  • Certification tips and exam structure

  • Key topics and revision strategies

  • Live doubt-clearing sessions and mentor support

Job Roles After Completing Azure AI Engineer & LUIS Online Training

  • Azure AI Engineer
    Design and deploy AI solutions using Azure Cognitive Services, Azure ML, and Bot Services.

  • Conversational AI Developer
    Build and implement intelligent chatbots and virtual assistants using LUIS and Azure Bot Framework.

  • NLP Engineer
    Work on natural language processing projects such as text classification, sentiment analysis, and entity recognition.

  • AI/ML Developer
    Develop end-to-end AI applications using Microsoft’s cloud ecosystem and integrate them into business solutions.

  • Machine Learning Engineer (Azure)
    Train, evaluate, and deploy machine learning models on Azure ML Studio or SDK.

  • Data Scientist – Azure Platform
    Use Azure tools to process large datasets, apply ML algorithms, and deliver actionable insights.

  • Azure Cognitive Services Specialist
    Implement and manage vision, language, speech, and decision APIs across applications.

  • Chatbot Developer
    Build bots for platforms like Teams, websites, and mobile apps using LUIS, QnA Maker, and Bot Framework.

  • Cloud AI Solution Architect
    Design enterprise AI architectures leveraging Azure AI and ensure integration, security, and scalability.

  • AI Consultant
    Help clients adopt Azure AI services effectively for digital transformation and process automation.

Azure Ai Engineer Course -Frequently Asked Questions (FAQs)

1. Who can take this course?
This course is ideal for software developers, data scientists, cloud engineers, AI/ML professionals, and freshers with basic programming knowledge who want to specialize in Azure AI services.

2. Do I need to know machine learning or Python before joining?
Basic knowledge of Python and machine learning concepts is helpful but not mandatory. The course covers foundational concepts before moving into advanced topics.

3. Is this course aligned with any certification?
Yes, the course is aligned with the Microsoft Certified: Azure AI Engineer Associate (AI-102) certification exam.

4. Will I work on real-time projects?
Yes, the course includes real-world projects such as chatbot development, image recognition, and text sentiment analysis using Azure services.

5. What tools and platforms will I learn?
You will learn to use Azure Cognitive Services, Azure Bot Framework, LUIS, Azure Machine Learning Studio, and Azure SDKs.

6. Is the training online or offline?
The course is delivered online through instructor-led sessions, recorded videos, and hands-on labs accessible via cloud platforms.

7. Will I receive a certificate after completion?
Yes, you will get a course completion certificate recognized by the industry.

8. Is placement assistance provided?
Yes, the course includes career support such as resume building, mock interviews, and job assistance.

9. How long is the course duration?
The typical course duration is 6–8 weeks depending on the batch type (weekday or weekend).

10. Can I get access to course content after completion?
Yes, you will receive lifetime access to course materials, project files, and recorded sessions.

Scroll to Top