Microsoft Course: Train models with scripts in Azure Machine Learning
Master Script-Based Model Training in Azure ML
- Convert exploratory notebooks into reproducible script-based workflows
- Execute parameterized training jobs in Azure ML
- Track and compare model metrics using MLflow
- Automate hyperparameter optimization with sweep jobs
- Prepare ML pipelines for CI/CD deployment
- Evaluate model performance systematically
- 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 1-hour 57-minute Azure Machine Learning course teaches production-ready techniques for training models using scripts. Through 3 practical modules, learners master converting Jupyter notebooks to executable scripts, tracking experiments with MLflow, and optimizing models via hyperparameter tuning. Designed for data engineers and ML practitioners, it bridges the gap between experimental code and scalable cloud workflows using command jobs and sweep jobs.
Microsoft's Train models with scripts in Azure Machine Learning course Outline
Learn the Train models with scripts in Azure Machine Learning
This hands-on Microsoft Learn path reveals how to productionize model training using Azure Machine Learning scripts. In under 2 hours, learn to automate hyperparameter tuning, track experiments like a pro with MLflow, and optimize resource usage – no more "works on my machine" scenarios. Click to transform your ML workflows from fragile to production-robust!
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Course Structure Includes:
Module 1: Script Execution (37 min)
- Notebook-to-script conversion
- Parameterized command jobs
- Cloud-based training orchestration
Module 2: Experiment Tracking (34 min)
- MLflow metric logging
- Model performance visualization
- Comparative analysis techniques
Module 3: Hyperparameter Optimization (46 min)
- Search space configuration
- Bayesian sampling strategies
- Cost-effective early termination
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 train production-grade ML models using Azure scripts: Convert notebooks, track experiments with MLflow, and optimize hyperparameters via sweep jobs. Includes hands-on tuning exercises.
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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