Azure AI Course Syllabus
in Hyderabad (2026) · All 30 Modules Explained
The Azure AI course syllabus at Azure AI Masters covers 30 modules in 5 phases — Azure and Python foundations, Azure AI services, generative AI with Azure OpenAI, Azure Machine Learning and MLOps, and real-time projects with AI-900 and AI-102 preparation — over about 3 months.
Questions running in your head right now
📚What exactly will I learn in this course?→🎓Is it okay for freshers and non-coders?→🛠️Which real-time projects will I build?→🏅Does it prepare me for AI-102?→📑 On this page
Azure AI course syllabus at a glance
30 modules, 5 phases, about 3 months — from your first Azure login to deployed AI projects.
Foundations
Modules 1–5: AI basics, Azure, maths, Python.
Azure AI services
Modules 6–14: Vision, Speech, Language and more.
Generative AI
Modules 15–19: Azure OpenAI and prompts.
Azure ML & MLOps
Modules 20–26: train, deploy, secure.
Projects & career
Modules 27–30: 3 projects, AI-102 prep.
Phase 1: AI, Azure and Python foundations
Start with what AI is, how Azure is organised and the maths and Python you need — so every later module makes sense.
📘 Modules in this phase
🛠️ What you’ll do
- Explore the Azure portal, resource groups and IAM.
- Compare Azure AI with AWS and Google AI services.
- Write Python with NumPy and Pandas in Jupyter and call the Azure SDK.
Phase 2: Azure AI services (Cognitive Services)
Learn the ready-made Azure AI services that power real apps — vision, face, speech, language, translation, Q&A, moderation and personalisation.
📘 Modules in this phase
🛠️ What you’ll do
- Call services through REST APIs and SDKs with secure keys.
- Build OCR, image tagging, speech-to-text and translation demos.
- Create a FAQ bot with Azure Question Answering.
Want to see these modules taught live? Sit in on a free demo class with our trainers.
Book a free demoPhase 3: Generative AI with Azure OpenAI
Work with GPT and DALL·E models on Azure OpenAI, master prompt engineering and build chatbots and content automation.
📘 Modules in this phase
🛠️ What you’ll do
- Deploy models and manage tokens and cost.
- Practise few-shot, zero-shot and chained prompts.
- Build an enterprise-style chatbot with memory and context.
Phase 4: Azure Machine Learning and MLOps
Go from data to deployed model with Azure Machine Learning Studio, then automate and secure it with MLOps.
📘 Modules in this phase
🛠️ What you’ll do
- Prepare and version data, train with AutoML and tune models.
- Evaluate with precision, recall, ROC curves and the Responsible AI dashboard.
- Deploy real-time and batch endpoints and set up CI/CD with Azure DevOps.
Phase 5: Real-time projects, career and certification
Put everything together in three projects, then prepare for AI-900 and AI-102, your resume, portfolio and interviews.
📘 Modules in this phase
🛠️ What you’ll do
- Build and deploy an Azure OpenAI chatbot.
- Build a vision app and an end-to-end predictive model API.
- Prepare your resume, portfolio and interview answers.
Complete Azure AI course syllabus — all 30 modules
Tap any module to see the topics it covers.
Module 1: Introduction to Azure AI
- What is Artificial Intelligence & Machine Learning
- Azure AI ecosystem overview
- Azure AI vs AWS AI vs Google AI
- Real-world AI use cases
- Azure AI services categories
Module 2: Azure Cloud Fundamentals for AI
- Azure portal & resource groups
- Regions, subscriptions, pricing basics
- Azure identity & access (IAM)
- Azure storage basics
- AI workloads architecture
Module 3: Azure AI Services Overview
- Cognitive Services overview
- Azure OpenAI overview
- Azure Machine Learning overview
- Decision services & analytics
- Responsible AI principles
Module 4: Data Basics for AI
- Optimization, Derivatives, Function, Probability,
- Scalar-Vector-Matrix, Vector Operation, Vector spaces.
Module 5: Python Basics for Azure AI
- Python fundamentals for AI
- Libraries: NumPy, Pandas
- Working with Azure SDK
- Virtual environments
- Jupyter notebooks
Module 6: Azure Cognitive Services Introduction
- Vision, Speech, Language, Decision services
- REST APIs & SDK usage
- Authentication & keys
- Endpoint management
- Cost optimization
Module 7: Azure Computer Vision
- Image analysis
- OCR (text extraction)
- Image tagging & description
- Face detection basics
- Real-time image processing
Module 8: Face API
- Face detection & recognition
- Face verification
- Emotion detection
- Privacy & ethics
- Real-world applications
Module 9: Azure Speech Services
- Speech-to-text
- Text-to-speech
- Speech translation
- Custom voice models
- Voice-enabled applications
Module 10: Azure Language Service
- Text analytics
- Sentiment analysis
- Key phrase extraction
- Entity recognition
- Language detection
Module 11: Azure Translator Service
- Text translation
- Document translation
- Speech translation
- Multi-language apps
- Global deployment strategy
Module 12: Azure Question Answering
- Knowledge base creation
- FAQ bots
- Custom QnA models
- Integration with chatbots
- Performance tuning
Module 13: Azure Content Moderator
- Text moderation
- Image moderation
- Video moderation
- Policy configuration
- Compliance scenarios
Module 14: Azure Personalizer
- Recommendation systems
- Reinforcement learning basics
- Personalization APIs
- User behavior modeling
- A/B testing
Module 15: Azure OpenAI Service
- GPT, DALL·E, Codex models
- Azure OpenAI vs OpenAI
- Model deployment
- Prompt structure
- Token & cost management
Module 16: Prompt Engineering
- Prompt design techniques
- System vs user prompts
- Few-shot & zero-shot learning
- Prompt chaining
- Prompt optimization
Module 17: Chatbots with Azure OpenAI
- Chat completion APIs
- Memory handling
- Context management
- Integration with web apps
- Enterprise chatbot design
Module 18: AI Image Generation
- DALL·E image creation
- Image editing & variations
- Responsible image usage
- Branding & creative use cases
- Automation workflows
Module 19: AI Content Automation
- AI-powered document generation
- Email & marketing automation
- Code generation use cases
- AI copilots
- Enterprise productivity tools
Module 20: Azure Machine Learning Studio
- Workspace creation
- Compute instances
- ML lifecycle
- Experiment tracking
- ML pipelines
Module 21: Data Preparation in Azure ML
- Data labeling
- Feature engineering
- Data versioning
- Data validation
- Dataset management
Module 22: Model Training
- Regression models
- Classification models
- Clustering
- AutoML
- Hyperparameter tuning
Module 23: Model Evaluation
- Accuracy, precision, recall
- Confusion matrix
- ROC curves
- Bias detection
- Responsible AI dashboard
Module 24: Model Deployment
- Real-time endpoints
- Batch inference
- REST APIs
- Containerization
- Scaling strategies
Module 25: MLOps with Azure
- CI/CD pipelines
- Model versioning
- Monitoring models
- Drift detection
- Azure DevOps integration
Module 26: Azure AI Security
- Data encryption
- Model security
- Identity management
- Compliance (GDPR, HIPAA)
- Risk mitigation
Module 27: AI Project – Chatbot
- Azure OpenAI chatbot
- FAQ automation
- Web integration
- Logging & analytics
- Deployment
Module 28: AI Project – Vision Application
- OCR-based document scanner
- Face recognition system
- Image classification app
- Real-time use case
- Performance tuning
Module 29: AI Project – Predictive Model
- End-to-end ML pipeline
- Data → Model → API
- Business use case
- Cost optimization
- Monitoring
Module 30: Career & Certification
- Azure AI Engineer roadmap
- AI-900 & AI-102 overview
- Resume & portfolio guidance
- Interview preparation
- Freelancing & enterprise roles
Real-time projects you build
🤖 Azure OpenAI chatbot
FAQ automation, web integration, logging & analytics and deployment.
Module 27👁️ Vision application
OCR document scanner, face recognition and image classification.
Module 28📈 Predictive model
End-to-end ML pipeline: data → model → API, with monitoring.
Module 29Who can join this course?
🎓 Students & freshers
Phase 1 starts from the basics, so no prior AI or cloud experience is needed.
💻 Developers
Add Azure AI services and Azure OpenAI to the apps you already build.
💼 Working professionals
Move into AI roles with projects and AI-102 aligned preparation.
Training modes
🏫 Classroom (Hyderabad)
Near JNTU Metro Station, Hyderabad — learn face to face with the trainer.
🌐 Live online
The same syllabus live online, from anywhere.
📞 Talk to us
Not sure which mode fits? Call +91 98824 98844.
Frequently asked questions
What is covered in the Azure AI course syllabus?
The Azure AI course syllabus at Azure AI Masters has 30 modules in five phases: Azure and Python foundations, Azure AI services (Vision, Speech, Language, Translator and more), generative AI with Azure OpenAI and prompt engineering, Azure Machine Learning and MLOps, and finally three hands-on projects with career and certification preparation.
How long is the Azure AI course in Hyderabad?
The course runs for about 3 months. It is available as classroom training in Hyderabad and as live online training, so you can choose the mode that fits your schedule.
Is the syllabus suitable for beginners?
Yes. The first phase covers AI basics, Azure cloud fundamentals, the maths you need for AI and Python basics, so students, freshers and people new to cloud can start from the beginning.
Which certifications does the syllabus prepare me for?
The syllabus is aligned with Microsoft AI-900 (Azure AI Fundamentals) and AI-102 (Azure AI Engineer Associate). Module 30 covers both exams along with your resume, portfolio and interview preparation. Always check the current exam skills outline on Microsoft Learn before booking.
Does the course include real-time projects?
Yes. Modules 27–29 are projects: an Azure OpenAI chatbot, a vision application (OCR document scanner, face recognition, image classification) and an end-to-end predictive model deployed as an API.
Do I need coding knowledge to join?
Basic coding helps but is not required. Module 5 teaches the Python you need for Azure AI, including NumPy, Pandas, the Azure SDK and Jupyter notebooks.
Start the Azure AI course with a free demo
Join Azure AI Masters in Hyderabad or live online — 3-month training with real-time projects, AI-102 & AZ-900 aligned preparation, internship support and placement assistance.