Azure Machine Learning Course
2026 guide · Syllabus, projects, DP-100 and careers
An Azure Machine Learning course teaches you to build, train, deploy and monitor ML models on Microsoft Azure — using Azure Machine Learning Studio, data preparation, AutoML, model evaluation, real-time and batch endpoints and MLOps — and prepares you for roles like ML Engineer and the DP-100 certification.
Questions running in your head right now
📚What does an Azure ML course cover?→🧑💻Is it right for me?→🏅Which certification goes with it?→💼What jobs can I get after it?→📑 On this page
What is Azure Machine Learning?
Azure Machine Learning is Microsoft’s platform for the full ML lifecycle — from data to deployed, monitored models.
🗂️ Workspace
The central place for data, experiments, models and endpoints.
⚙️ Compute
Compute instances for development and clusters for training.
🤖 AutoML & designer
Train models automatically or with a drag-and-drop designer.
📈 Tracking
Log metrics and compare runs with MLflow-based tracking.
🚀 Endpoints
Deploy models as real-time or batch endpoints.
🔁 MLOps
Pipelines, versioning, CI/CD and monitoring.
What an Azure Machine Learning course covers
This is how the Azure ML modules in our Azure AI course syllabus are organised:
| Module | Topics |
|---|---|
| Azure Machine Learning Studio | Workspace creation, compute instances, ML lifecycle, experiment tracking, ML pipelines |
| Data preparation | Data labelling, feature engineering, data versioning, validation, dataset management |
| Model training | Regression, classification, clustering, AutoML, hyperparameter tuning |
| Model evaluation | Accuracy, precision, recall, confusion matrix, ROC curves, bias detection, Responsible AI dashboard |
| Model deployment | Real-time endpoints, batch inference, REST APIs, containerisation, scaling |
| MLOps with Azure | CI/CD pipelines, model versioning, monitoring, drift detection, Azure DevOps integration |
Projects you build
📈 Predictive model API
An end-to-end pipeline: data → model → deployed REST API.
End to end🧪 AutoML experiment
Compare models automatically and pick the best one.
AutoML🔁 MLOps pipeline
Automated retraining and deployment with monitoring.
MLOpsWant to see Azure ML taught live? Join a free demo class and build your first experiment with a trainer.
Book a free demoWho should take an Azure Machine Learning course?
🎓 Freshers with Python
Start an ML career on a cloud platform companies use.
📊 Data analysts
Move from reports to predictive models.
💻 Developers
Add ML models to apps and deploy them on Azure.
☁️ Cloud engineers
Run and scale ML workloads on Azure.
🔬 Data scientists
Move notebooks into production with MLOps.
🔁 Career switchers
A structured path into ML engineering.
Prerequisites and skills you gain
📋 Helpful before you start
🎯 Skills you gain
- Train and tune models with AutoML and code.
- Evaluate models with the right metrics.
- Deploy, monitor and retrain models with MLOps.
Which certification goes with an Azure ML course?
DP-100
Azure Data Scientist Associate — focused on designing and running ML solutions on Azure.
Main ML examAI-900
Azure AI Fundamentals — a good first step for beginners.
FoundationAI-102
Azure AI Engineer Associate — if you also work with Azure AI services and Azure OpenAI.
RelatedCareers after an Azure Machine Learning course
- Azure Machine Learning Engineer — builds and deploys models.
- MLOps Engineer — automates training, deployment and monitoring.
- Data Scientist — builds predictive models for business problems.
- AI Engineer — combines ML with Azure AI services and generative AI.
Frequently asked questions
What is taught in an Azure Machine Learning course?
Azure Machine Learning Studio, data preparation, model training with AutoML and code, model evaluation, real-time and batch deployment, and MLOps with CI/CD, versioning and monitoring.
Do I need coding for an Azure ML course?
Basic Python helps a lot. AutoML and the designer reduce coding, but most real projects and MLOps tasks use Python.
Which certification is best after an Azure ML course?
DP-100 (Azure Data Scientist Associate) is the main Azure certification for machine learning. AI-900 is a good starting point for beginners.
How long does an Azure Machine Learning course take?
It depends on the depth of the course. Azure ML is usually covered over several weeks within a longer Azure AI or data science program.
What is the difference between Azure ML and Azure AI services?
Azure AI services are ready-made APIs for vision, language and speech. Azure Machine Learning is for building, training and deploying your own custom models.
What jobs can I get after learning Azure ML?
Roles such as Azure Machine Learning Engineer, MLOps Engineer, Data Scientist and AI Engineer.
Learn Azure AI with a trainer by your side
Join Azure AI Masters in Hyderabad (near JNTU Metro Station) or live online — 3-month training with real-time projects, AI-102 & AZ-900 aligned preparation, internship support and placement assistance.