Azure Data Scientist Associate DP-100 Exam Practice Tests

Udemy MOOC / Non-credit USD 19.99
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Azure Data Scientist Associate DP-100 Exam Practice Tests

About this course

Welcome to the immersive journey towards mastering Azure Data Science and acing the DP-100 certification exam. Our comprehensive course is meticulously designed to propel your skills in Azure Machine Learning to new heights.Course Overview: Step into the world of Azure Data Science and become proficient in managing, building, and deploying machine learning models using the Azure ecosystem. This course amalgamates theoretical learning with hands-on practical exercises, aligning with the DP-100 exam objectives.What You'll Learn:Explore Azure ML: Delve into Azure Machine Learning, understanding its workspace, data management, and compute configurations.Model Creation: Learn to craft machine learning models using Azure ML Designer, notebooks, and automated machine learning.Hyperparameter Tuning: Discover the art of fine-tuning model performance with Azure ML's hyperparameter optimization.Model Deployment: Master the deployment of models, covering various strategies like A/B testing and blue-green deployments.MLOps Practices: Understand machine learning operations, encompassing CI/CD, model monitoring, governance, and versioning.Why Choose Our Course: Experience a blend of engaging lectures, real-world scenarios, and hands-on labs curated to simulate the DP-100 exam environment. Benefit from our expert guidance, comprehensive study materials, and practical exercises aimed at solidifying your understanding of Azure Data Science.Who Is This For: This course caters to aspiring data scientists, machine learning enthusiasts, and professionals aiming to validate their Azure ML skills with the DP-100 certification. Whether you're new to Azure or seeking to enhance your expertise, this course equips you for success.Prepare to excel in the DP-100 e

What you'll learn

  • Understanding the Azure Machine Learning workspace
  • Creating machine learning models using Azure ML Designer and notebooks
  • Performing hyperparameter tuning for model optimization
  • Deploying models using various strategies like A/B testing
  • Implementing MLOps practices including CI/CD and model governance

Skills you'll gain

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