MLOps with Data Version Control: Getting Started

MLOps 2023    |    Beginner
  • 16 videos | 1h 51m 48s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Data Version Control (DVC) is a technology that simplifies and enhances data versioning and management. It provides Git-like capabilities to track, share, and reproduce changes in data while optimizing storage and facilitating collaboration in data-centric projects. In this course, you will discover how DVC simplifies the intricate components of ML projects - code, configuration files, data, and model artifacts. Next, you will embark on hands-on DVC exploration by installing Git locally and establishing a remote repository on GitHub. Then you will install DVC, set up a local repository, configure DVC remote storage, and add and track data using DVC. Finally, you will create Python-based machine learning (ML) models and track them with DVC and Git integration. You will create metafiles pointing to DVC-stored data and artifacts and commit these files to GitHub, tagging different model and data versions. Through Git tags, you will access specific model iterations for your work. This course will empower you with theoretical insights and practical proficiency in employing DVC and Git.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline key concepts of dvc
    Describe the features of git
    Describe the features of dvc
    Install git on your local machine
    Install dvc on your local machine
    Create a git local repository
    Connect to a remote github repo from git
  • Configure a remote storage configuration in dvc
    Push a file to dvc remote storage
    Create and serialize an ml model
    Push and commit a model to dvc and git
    View the files that github tracks
    Run and push a different model version
    Revert to previous code versions in git
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 4s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 10m 26s
    After completing this video, you will be able to outline key concepts of DVC. FREE ACCESS
  • Locked
    3.  A Brief Overview of Git
    7m 49s
    Upon completion of this video, you will be able to describe the features of Git. FREE ACCESS
  • Locked
    4.  DVC Concepts
    7m 14s
    After completing this video, you will be able to describe the features of DVC. FREE ACCESS
  • Locked
    5.  Installing Git
    4m 56s
    Learn how to install Git on your local machine. FREE ACCESS
  • Locked
    6.  Installing DVC
    7m 4s
    In this video, find out how to install DVC on your local machine. FREE ACCESS
  • Locked
    7.  Creating a Git Local Repository
    9m 6s
    During this video, discover how to create a Git local repository. FREE ACCESS
  • Locked
    8.  Connecting to GitHub from Git
    8m 2s
    In this video, you will learn how to connect to a remote GitHub repo from Git. FREE ACCESS
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    9.  Configuring a Remote Storage Configuration in DVC
    7m 10s
    Discover how to configure a remote storage configuration in DVC. FREE ACCESS
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    10.  Pushing Files to DVC Remote Storage
    6m 17s
    Find out how to push a file to DVC remote storage. FREE ACCESS
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    11.  Creating a Machine Learning (ML) Model in Python
    8m 10s
    During this video, you will learn how to create and serialize an ML model. FREE ACCESS
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    12.  Pushing an ML Model to DVC and Git
    8m 58s
    In this video, discover how to push and commit a model to DVC and Git. FREE ACCESS
  • Locked
    13.  Viewing the Files Committed to GitHub
    4m 7s
    Find out how to view the files that GitHub tracks. FREE ACCESS
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    14.  Running and Pushing a Different Model Version
    9m 22s
    During this video, you will learn how to run and push a different model version. FREE ACCESS
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    15.  Reverting to Previous Code Versions in Git
    9m 5s
    Discover how to revert to previous code versions in Git. FREE ACCESS
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    16.  Course Summary
    2m
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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