AWS Certified Machine Learning: Data Preparation & SageMaker Security

Amazon Web Services 2021    |    Intermediate
  • 12 Videos | 42m 26s
  • Includes Assessment
  • Earns a Badge
Building successful machine learning (ML) applications require the transformation of raw data, such that it meets the requirements of individual ML algorithms. Explore how to prepare data using Amazon SageMaker and S3 and create security services for this data through this course. Start by delving deeper into summary statistics and visualization​ before moving on to security best practices for Amazon SageMaker. You'll also examine Amazon CloudWatch and Amazon CloudTrail in greater detail. After taking this course, you'll have a solid grasp of various data formats, data security practices, and monitoring and alerting services used in SageMaker. You'll also have the knowledge to prepare data for machine learning and take a step further in your preparation for the AWS Certified Machine Learning – Specialty certification exam.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    use summary statistics to perform data preparation for an Amazon Reviews dataset
    perform visualization for data preparation of an Amazon Reviews dataset
    recognize the difference between various SageMaker data formats
    convert a data frame to a sparse matrix
    outline how to create S3 buckets for data storage
  • work with Amazon Ground Truth for data labeling jobs
    describe the at rest and in-transit encryption approaches used for security in SageMaker
    work with SageMaker data accessing approaches, including VPCs, IAM, logs, and monitoring
    describe how to monitor an AWS system using CloudWatch
    outline how to record API activity using CloudTrail
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m
    UP NEXT
  • Playable
    2. 
    Working with Summary Statistics
    4m 9s
  • Locked
    3. 
    Performing Visualization
    4m 3s
  • Locked
    4. 
    Data Formats for Amazon SageMaker
    3m 28s
  • Locked
    5. 
    Converting a Dataset to Sparse Matrix
    2m 56s
  • Locked
    6. 
    Creating S3 Buckets
    3m 7s
  • Locked
    7. 
    Labelling Data with Amazon Ground Truth
    2m 54s
  • Locked
    8. 
    SageMaker Security: Encryption
    5m 49s
  • Locked
    9. 
    Exploring Amazon SageMaker Security
    3m 4s
  • Locked
    10. 
    Characteristics and Advantages of Amazon CloudWatch
    3m 40s
  • Locked
    11. 
    Characteristics and Advantages of Amazon CloudTrail
    2m 42s
  • Locked
    12. 
    Course Summary
    35s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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