Microsoft Course: Deploy and consume models with Azure Machine Learning
From Code to Cloud: Master Azure ML Model Deployment
- Deploy ML models to both real-time and batch endpoints in Azure
- Optimize model performance for production environments
- Automate batch scoring workflows for large datasets
- Implement best practices for testing and troubleshooting deployments
- Streamline collaboration using MLflow integration
- Align with industry
- Build a base for specialized roles in AI development or cloud engineering
- Prepare for more advanced Microsoft certifications in AI
What you will learn
This course, "Manage and Review Models in Azure Machine Learning," equips learners with essential skills to streamline model management and evaluation using Azure Machine Learning. Over two modules, you'll learn to log and register MLflow models for version control and reproducibility, and explore Responsible AI tools to assess model fairness, transparency, and reliability. Designed for data professionals, this 1-hour 22-minute training combines hands-on exercises with practical insights to optimize model workflows and align with ethical AI practices.
Microsoft's Deploy and consume models with Azure Machine Learning course Outline
Learn the Deploy and consume models with Azure Machine Learning
Looking to deploy machine learning models seamlessly in Azure? This hands-on course teaches you to set up real-time and batch endpoints for scalable predictions. With step-by-step exercises on MLflow integration and deployment best practices, you'll gain the skills to operationalize models confidently. Perfect for data scientists and developers—click here to master
Start your journey today:
Course Structure Includes:
Module 1: Deploy to Managed Online Endpoints (45 min)
- Real-time inferencing fundamentals
- MLflow model deployment
- Endpoint testing and monitoring
Module 2: Batch Endpoint Deployment (44 min)
- Batch scoring workflows
- Custom model deployment
- Troubleshooting batch jobs
Includes 2 practical exercises and assessments.
Training Options
Self Paced Learning
- Lifelong access to high-quality content
- Curated by industry experts
- Customized learning progress
- 24/7 learner assistance and support
- Follow the latest technology trends
Exam Dump
- 100% Real Exam Practice Tests
- 100% Verified Exam Questions & Answers
- 100% Guarantee Passing Rate
- Average 7 Days to Practice & Pass
Description
Learn to deploy models to real-time and batch endpoints in Azure Machine Learning. Gain hands-on skills for MLflow integration, testing, and scalable predictions.
Pre-requisites
None
SPOTO Empowers You to Earn Your Certification.
Benefits of AWS Certified AI Practitioner Certification
Microsoft Certified: Azure AI Fundamentals (AI-900) is an entry-level certification designed to validate foundational knowledge of AI and machine learning concepts, including computer vision, natural language processing (NLP), generative AI, and responsible AI principles. Ideal for both technical and non-technical professionals, it requires no prior coding experience and offers free, flexible learning resources via Microsoft Learn. The certification enhances career prospects in high-demand roles like AI Engineer or Data Scientist, with potential salary increases up to 20%, while serving as a gateway to advanced Azure certifications (e.g., AI-102). Cost-effective and time-efficient (preparation in 10–30 hours), the exam focuses on real-world applications using Azure Cognitive Services, OpenAI APIs, and Azure Machine Learning. With permanent validity and global recognition across 90+ countries, it equips professionals to drive AI innovation in industries such as healthcare and finance. Start your AI journey with Microsoft Learn today!
Advantages of Using SPOTO's Exam Preparation Materials
SPOTO's study resources provide comprehensive coverage of the exam syllabus, aligning with key topics like ML problem framing, data processing, model optimization, and pipeline automation. The materials include structured learning paths, practice exams, and real-world case studies that mirror the certification's focus on designing, implementing, and deploying machine learning solutions with Microsoft services and ML workflows. By leveraging SPOTO's targeted content, candidates can efficiently bridge knowledge gaps, reinforce practical skills, and gain familiarity with the exam format. This focused preparation increases confidence and readiness, particularly for complex tasks such as deploying CI/CD pipelines or optimizing model performance—areas emphasized in the certification. Combined with hands-on experience, SPOTO's resources offer a strategic advantage for achieving certification success.
Online Learning Community
Click to join the online learning community and learn AI knowledge:
https://chat.whatsapp.com/Fc9f29Bd0SQAMeDThBFdpY