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Batch Date: Apr 21st @7:00AM

Faculty: Mr. Sekhar Reddy (15+ Yrs of Exp,.. & Real Time Expert)

Duration: 60 Days

Venue :
DURGA SOFTWARE SOLUTIONS,
Flat No : 202, 2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038

Ph.No: +91- 9246212143, 80 96 96 96 96

Syllabus:

AI-900: Azure AI Fundamentals -

Introduction to AI & Microsoft Azure AI

Focus: Foundations of AI and How Microsoft supports it through Azure.

Course Overview & AI Fundamentals

• What is Artificial Intelligence?
• Types of AI: Narrow, General, Super AI
• AI in real-life use cases
• AI, ML, and DL differences

Introduction to Machine Learning

• Supervised, Unsupervised, Reinforcement learning
• Common ML scenarios
• Demo: Azure ML Studio UI overview

Microsoft Azure AI Platform Overview

• What is Azure AI?
• Azure services: ML, Cognitive Services, Bot Services
• Demo: Navigating Azure Portal

Responsible AI

• Ethics in AI
• Bias, fairness, transparency
• Microsoft's Responsible AI principles

Machine Learning in Azure

Focus: Azure ML concepts and tools

Azure Machine Learning Basics

• What is Azure ML?
• Workspaces, datasets, compute resources

 ML Model Lifecycle

• Data prep, training, evaluation, deployment
• Tools: Designer vs. SDK

Automated Machine Learning (AutoML)

• Concept and benefits
• Demo: AutoML in Azure ML Studio

ML Designer in Azure ML

• Drag-and-drop ML model creation
• Demo: Create a simple classification model

Quiz + Hands-on Lab

• Scenario-based questions
• Practice: Train and deploy a model with Azure ML Designer

Computer Vision & NLP

Focus: Cognitive Services for Vision and Language

Introduction to Azure Cognitive Services

• What are Cognitive Services?
• Categories: Vision, Language, Speech, Decision

Computer Vision Basics

• Image classification, object detection
• Demo: Use Computer Vision API for image analysis

Facial Recognition

• Face API features
• Demo: Detect and identify faces

Natural Language Processing (NLP) Basics

• Text analytics, entity recognition, sentiment analysis
• Demo: Use Text Analytics API

Conversational AI & Decision Services

Focus: Language models, bots, decision-making services

Conversational AI Overview

• What is Conversational AI?
• Building blocks of a chatbot

Azure Bot Service + QnA Maker

• QnA Maker overview (now Azure AI QnA)
• Demo: Create a simple QnA bot

Language Understanding (LUIS)

• What is LUIS?
• Intents, utterances, entities
• Demo: Build a LUIS app

Azure OpenAI Overview (Optional for AI-900 but useful)

• Introduction to GPT models
• Use cases: summarization, content generation

Decision Services

• Content Moderator, Anomaly Detector, Personalizer
• Demo: Personalizer in action

Integration, Practice & Exam Prep

Focus: Applying knowledge, mock tests, and confidence-building

Integrating AI into Apps

• REST APIs and SDKs
• Hands-on: Connect AI services with Power Apps or a basic web app

Real-World Use Cases

• Industry scenarios: Healthcare, Finance, Retail, Manufacturing

Responsible AI Deep Dive

• How to implement fairness, interpretability, privacy

Focus: Certification tips, live Q&A, review

Study Plan & Last-Minute Tips

• How to approach the AI-900 exam
• Resources & Microsoft Learn paths

AI-102: Designing and Implementing an Azure AI

Build foundational understanding of Azure AI services and solutions.

AI-102 Overview & Certification Scope

• Certification objectives
• Required skills and knowledge
• Study resources & learning path

Overview of Azure AI Services

• Categories: Vision, Speech, Language, Decision, Azure OpenAI
• Cognitive Services vs. Azure Machine Learning

Azure AI Workloads

• Common workloads (NLP, vision, forecasting, chatbots)
• Choosing the right Azure AI service

Setting up Azure Environment

• Azure portal, Azure CLI, Resource groups
• Create Cognitive Services resource

Responsible AI & Security

• Ethics in AI
• Role-based access, key management
• Responsible AI tools in Azure

Natural Language Processing

Goal: Learn to build NLP solutions using Azure Cognitive Services

Text Analytics

• Sentiment analysis, key phrase extraction, named entity recognition
• Hands-on: Use Text Analytics REST API / SDK

Language Understanding with Azure Language Studio

• Intents, entities, utterances
• Create and train a Language Understanding model

Custom Text Classification and Named Entity Recognition

• Use Custom Text features
• Hands-on: Train & deploy custom models

Translation and Language Detection

• Translator service overview
• Hands-on: Build real-time translation app

Computer Vision

Goal: Understand image analysis, OCR, facial recognition,
and custom vision

Computer Vision Basics

• Image analysis, OCR, spatial analysis
• Hands-on: Use Computer Vision API

Day 12: Optical Character Recognition (OCR) and Form Recognizer

• Extracting data from forms
• Hands-on: Train Form Recognizer for custom layout

Face API

• Detect, verify, and identify faces
• Hands-on: Create a face detection solution

Custom Vision

• Train a custom image classifier
• Hands-on: Use Custom Vision portal & SDK

Vision Use Case + Lab

• Use Case: Smart access control system with face ID
• Lab assignment

Speech Services

Goal: Implement speech-enabled applications

Speech to Text

• Real-time and batch transcription
• Hands-on: Transcribe audio using Speech SDK

Text to Speech

• Neural voices, SSML
• Hands-on: Convert text to speech with customization

Speech Translation

• Build multilingual apps
• Hands-on: Build a language translator app

Custom Speech

• Train custom speech models
• Use Case: Call center transcription with domain-specific vocabulary

Review + Quiz

• Speech services recap
• Quiz + case study discussion

Conversational AI & Bot Framework

Goal: Design and deploy intelligent bots

Introduction to Bot Framework & Azure Bot Service

• Architecture, Webchat, Channels
• Tools: Composer, CLI, Emulator

Build Bots with Composer

• Create dialogs, use triggers and properties
• Hands-on: Build a QnA-style bot

Integrate LUIS & QnA in Bots

• Improve language understanding in bots
• Hands-on: Add NLP to bots

Deploy Bots to Azure

• Web App Bot deployment
• Configure channels like Teams or Web Chat

Real World Bot Use Case

• Use Case: HR Bot for internal employee queries
• Group activity or lab

Azure OpenAI, Decision Services & Final Prep

Goal: Work with modern generative AI models
and complete certification preparation

Azure OpenAI Basics

• GPT models, Prompt Engineering, Use cases
• Hands-on: Generate content using OpenAI APIs

Decision Services

• Personalizer, Content Moderator, Anomaly Detector
• Use Case: Personalized news feed / moderation

Integrate Multiple AI Services

• End-to-end pipeline combining Vision, NLP, and Bots
• Hands-on: Smart customer support platform