Azure Data Scientist Associate: Machine Learning

Azure 2021
  • 11 Videos | 1h 8m 30s
  • Includes Assessment
  • Earns a Badge
Machine Learning uses real data to train algorithms that can be used for anomaly detection, computer vision, and natural language processing. In this course, you'll learn about datasets and how to manipulate data for them. Next, you'll learn the difference between labeled and unlabeled data and why some AI models require labeled data. You'll examine the features that should be used for a selected dataset. Next, you'll learn about the types of machine learning algorithms that are available, including regression algorithms, classification algorithms, and clustering algorithms. Finally, you'll explore the difference between supervised and unsupervised machine learning models. This course is one in a collection that prepares learners for the Designing and Implementing a Data Science Solution on Azure (DP-100) exam.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe machine learning and how it can be used for anomaly detection, computer vision, and natural language processing
    describe datasets and how to manipulate data for those datasets
    describe the difference between labeled and unlabeled data and why some AI models require labeled data
    describe how features are selected and used from datasets in AI algorithms
    describe regression algorithms and how they are used to make predictions
  • describe classification algorithms and how they are used to classify objects or relations
    describe clustering algorithms and how they can be used to determine groupings in data
    describe how supervised machine learning models use labeled data, are simpler to build, and have more accurate results
    describe how unsupervised machine learning models discover patterns from unlabelled data and can perform complex processing tasks
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 44s
    UP NEXT
  • Playable
    2. 
    Machine Learning
    7m 58s
  • Locked
    3. 
    Data Manipulation and Datasets
    7m 57s
  • Locked
    4. 
    Labeled and Unlabeled Data
    5m 29s
  • Locked
    5. 
    Data Features
    8m 38s
  • Locked
    6. 
    Machine Learning Regression Algorithms
    7m 23s
  • Locked
    7. 
    Machine Learning Classification Algorithms
    6m 30s
  • Locked
    8. 
    Machine Learning Clustering Algorithms
    6m 46s
  • Locked
    9. 
    Supervised Machine Learning
    7m 56s
  • Locked
    10. 
    Unsupervised Machine Learning
    7m 22s
  • Locked
    11. 
    Course Summary
    47s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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