Microsoft Course: Manage and review models in Azure Machine Learning
Master Model Management & Ethical AI in Azure Machine Learning
- Master MLflow integration for seamless model tracking and registration
- Gain expertise in evaluating models using Responsible AI dashboards
- Improve reproducibility and compliance in machine learning workflows
- Enhance transparency and fairness in model decision-making
- Strengthen your ability to debug models and generate actionable insights
- 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 Develop solutions with Azure AI Document Intelligence course Outline
Learn the Develop solutions with Azure AI Document Intelligence
Struggling with model management or ethical AI compliance? Dive into Microsoft's "Manage and Review Models in Azure Machine Learning" course to master MLflow for version control and leverage Responsible AI tools for model evaluation. With step-by-step modules, hands-on exercises, and expert guidance, this training simplifies complex workflows while ensuring your models are transparent and reliable. Ready to elevate your ML expertise? Explore the course now and transform how you build, track, and audit AI solutions.
Start your journey today:
Course Structure Includes:
Module 1: Register an MLflow Model in Azure Machine Learning (40 min)
- Logging models with MLflow.
- Understanding MLflow model formats.
- Registering models for version control.
- Hands-on exercise for logging/registering models.
Module 2: Create and Explore the Responsible AI Dashboard (42 min)
- Introduction to Responsible AI principles.
- Building and interpreting Responsible AI dashboards.
- Evaluating model fairness, errors, and counterfactuals.
- Practical exercise using Python SDK v2.
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 track models with MLflow and evaluate fairness using Responsible AI tools in Azure. Perfect for data pros aiming to optimize workflows and ensure ethical AI practices.
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.
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