Azure Machine Learning enables building, training, deploying, and managing machine learning models at scale using Microsoft Azure’s enterprise-grade cloud platform.
Azure Machine Learning enables building, training, deploying, and managing machine learning models at scale using Microsoft Azure’s enterprise-grade cloud platform.
Level
Advanced
Duration
8 weeks
















Azure Machine Learning is a comprehensive cloud-based service that enables data scientists, machine learning engineers, and developers to build, train, deploy, and manage machine learning models efficiently. This course on Jast Tech is designed to provide in-depth knowledge of Azure Machine Learning Studio, automated machine learning, model lifecycle management, and MLOps practices. Learners will gain hands-on experience with data preparation, feature engineering, experiment tracking, model training using Python and popular frameworks, and scalable deployment using Azure services. The curriculum covers both no-code and code-first approaches, making it suitable for beginners as well as experienced professionals. Real-world use cases are emphasized to help learners understand enterprise-grade ML workflows, security, monitoring, and performance optimization in the Azure ecosystem. By the end of this training, participants will be able to design end-to-end machine learning solutions, integrate models with business applications, and confidently work on cloud-based ML projects aligned with industry standards.
Azure Machine Learning is a comprehensive cloud-based service that enables data scientists, machine learning engineers, and developers to build, train, deploy, and manage machine learning models efficiently. This course on Jast Tech is designed to provide in-depth knowledge of Azure Machine Learning Studio, automated machine learning, model lifecycle management, and MLOps practices. Learners will gain hands-on experience with data preparation, feature engineering, experiment tracking, model training using Python and popular frameworks, and scalable deployment using Azure services. The curriculum covers both no-code and code-first approaches, making it suitable for beginners as well as experienced professionals. Real-world use cases are emphasized to help learners understand enterprise-grade ML workflows, security, monitoring, and performance optimization in the Azure ecosystem. By the end of this training, participants will be able to design end-to-end machine learning solutions, integrate models with business applications, and confidently work on cloud-based ML projects aligned with industry standards.
Job Roles You Can Achieve
After completing this course
Introduction to Azure Machine Learning
This module introduces Azure Machine Learning, its core capabilities, and how it fits into the Azure ecosystem for enterprise AI solutions.
Azure ML Workspace and Resources
Learners understand how to set up and manage workspaces, compute targets, and supporting resources required for ML development.
Data Preparation and Management
This module focuses on handling structured and unstructured data efficiently for machine learning pipelines.
Experiments and Training Models
Covers model training workflows, experiment management, and performance evaluation.
Automated Machine Learning (AutoML)
Learners explore automated model selection and hyperparameter tuning for faster development.
Seven intentional milestones — from first session to dream job.
Select a schedule that works best for you
Starts
22 Aug 2026
Time
09:30 AM – 12:30 PM
Duration
8 weeks
Starts
24 Aug 2026
Time
07:00 AM – 09:00 AM
Duration
8 weeks
Starts
29 Aug 2026
Time
02:00 PM – 05:00 PM
Duration
8 weeks
Starts
31 Aug 2026
Time
08:00 PM – 10:00 PM
Duration
8 weeks
Our team will craft the perfect batch for you.
Real Feedback from our clients
Round-the-clock assistance
Professional profile building
Expert resume crafting
Mentorship from graduates
Mock interviews & tips
Real-world experience



See how we stand out from the competition
Well-structured, up-to-date curriculum designed by industry experts to build strong fundamentals and advanced knowledge.
Outdated or incomplete curriculum that may not cover current industry needs.
Extensive practical sessions, live demos, and hands-on exercises to ensure real learning.
Limited practical exposure with theory-heavy teaching approach.
Learn from certified professionals with years of industry experience and teaching expertise.
Instructors with limited industry experience or practical knowledge.
Work on real-world projects that enhance problem-solving skills and build a strong portfolio.
Lack of real-world projects or unrealistic practice examples.
Regular assignments, quizzes, and assessments to track progress and strengthen concepts.
Irregular assessments or no proper evaluation of learning.
Resume building, interview preparation, and placement assistance to boost your career.
Limited or no career support and placement assistance.
24/7 doubt resolution and personalized guidance from instructors whenever you need it.
Slow doubt resolution or limited support availability.
Industry-recognized certificate that validates your skills and enhances your career opportunities.
Certificates with little industry value or recognition.
Lifetime access to course content, recordings, and resources even after completing the course.
Limited access duration with extra charges for resources.
High-quality training at affordable prices with no hidden costs and flexible payment options.
High course fees with hidden charges and no flexibility.
Azure Machine Learning – Associate
130 minutes
Multiple Choice & Multi-Response
720 (Scale: 100–1000)
Associate

Prepare
Curated questions with expert answers to help you ace your next interview.
Q1. What is Azure Machine Learning?
Azure Machine Learning is a cloud service that enables building, training, deploying, and managing machine learning models at scale.
Q2. What is an Azure ML Workspace?
It is the top-level resource that organizes experiments, models, compute, datasets, and endpoints.
Q3. What is AutoML in Azure?
AutoML automatically selects algorithms and tunes hyperparameters to produce the best-performing model.
Q4. How does Azure ML support MLOps?
It integrates with CI/CD pipelines, supports model versioning, monitoring, and automated retraining.
Q5. What deployment options are available in Azure ML?
Azure ML supports real-time endpoints, batch inference, and deployment using containers and Kubernetes.
Support
Can't find what you're looking for? Reach out to our support team anytime.
Q1. Who should take this course?
This course is ideal for data scientists, ML engineers, cloud professionals, and developers aiming to build ML solutions on Azure.
Q2. Do I need prior machine learning knowledge?
Basic ML concepts and Python knowledge are recommended, but foundational topics are also covered.
Q3. Is this course hands-on?
Yes, it includes practical labs and real-world scenarios using Azure Machine Learning.
Q4. Does this course cover AutoML and MLOps?
Yes, both Automated ML and MLOps practices are covered in detail.
Q5. Will this help with Azure certifications?
Yes, it aligns well with Azure AI and Data Science certification paths.
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JastTech
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JastTech
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JastTech
Training & Development Center
91 Springboard Business Hub ,Madhapur LVS Arcade, 71, Jubilee Enclave, HITEC City, Hyderabad,India Telangana 500081
JastTech
Training & Development Center
Sr. No. 30/2/1, 3rd Floor, Above Rajrshi Shahu Bank & BOB Balaji Nagar, Dhankawadi, Katraj, Pune, Maharashtra 411043
JastTech
Training & Development Center
Millenium City - Tower I, Salt Lake, Kolkata, West Bengal 700091
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