Azure Machine Learning
With Techpratham, you can learn how to design, build, and deploy ML models on the cloud using Azure Machine Learning. Get real-world experience with automated ML, pipelines, and MLOps integration.
Level
Advanced
Duration
8 weeks
Placement Client
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About Azure Machine Learning
Techpratham’s Azure Machine Learning Training equips learners with cloud-based machine learning expertise. You’ll explore Azure ML Studio, data preparation, model training, deployment, and monitoring in real-time. The course covers AutoML, pipelines, responsible AI practices, and integration with MLOps. By the end, you’ll be able to build scalable ML solutions and deploy enterprise-ready AI applications on Azure.
Training Plan
About trainer
Working professional who is carrying more then 10 years of industry experience.
Decks & Updated Content
Access to updated presentation decks shared during live training sessions.
e-Book
E-book provided by TechPratham. All rights reserved.
Assignments & MCQs
Module-wise assignments and MCQs provided for practice.
Video Recording
Daily Session would be recorded and shared to the candidate.
Projects
Live projects will be provided for hands-on practice.
Resume Building
Expert-guided resume building with industry-focused content support.
Interview Preparation
Comprehensive interview preparation with real-time scenario practice.
Azure Machine Learning
Course Curriculum
Introduction to Azure Machine Learning
Get started with Azure ML concepts and platform overview.
Azure ML Workspace & Setup
Set up and configure an Azure ML workspace, understand its components, and manage compute resources effectively.
Data Preparation & Management
Learn how to import, clean, and preprocess datasets using Azure ML Studio and SDK for better model training.
Model Development with Azure ML
Build machine learning models using Azure ML Designer, AutoML, and Jupyter Notebooks.
Training & Hyperparameter Tuning
Train ML models at scale using Azure ML pipelines and optimize them with hyperparameter tuning techniques.
Model Deployment & Serving
Deploy machine learning models as REST APIs or endpoints for real-time and batch inference.
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Who Should Take Azure Machine Learning
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Working Professionals
Ops/Administrators/HR
Developers
BA/QA Engineers
Cloud / Infra
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Key Projects
<h1><strong>Azure Machine Learning</strong></h1>
Customer Churn Prediction using AutoML
Train a lot of models on a customer dataset with Azure ML AutoML. Set up the best model as a real-time endpoint and see how well it works at predicting customer churn in a telecom company.
AI-Powered Image Classification on Azure
Use Azure ML to make a deep learning model that can sort images, like medical scans or product photos. As a scalable API service, use pipelines to preprocess, train, and deploy the model.
MLOps Workflow for Fraud Detection
Create a way to find fraud that keeps getting better over time. Use GitHub and Azure DevOps to set up CI/CD, keep an eye on how well your model works, and make sure you get alerts for problems right away.
Placement Process
Live Class with Industry Use Cases
- Interactive learning
- Real-world examples
- Expert guidance
- Doubt resolution
Daily Assignment & Weekly Assessments
- Hands-on practice
- Concept reinforcement
- Weekly evaluation
- Timely feedback
Project Testing & Deployment
- Project development
- Testing practice
- Deployment exposure
- Portfolio creation
Interview Preparation (Mock, PD, Alumni Session)
- Mock interviews
- Personal development
- Alumni guidance
- Confidence building
Resume Building
- Resume crafting
- Industry-focused format
- Skills highlighting
- Professional presentation
Placement
- Job assistance
- Interview support
- Career guidance
- Opportunity access
Knowledge Center
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What Makes TechPratham Training Different?
Course FAQs
Why should I learn Azure Machine Learning when I already know Python ML libraries?
What is Azure Machine Learning?
Why should I use Azure Machine Learning?
Do I need coding experience for Azure Machine Learning?
What are the main use cases of Azure ML?
How does Azure ML support MLOps?
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