Cloud Computing and MLOps: Introduction to MLOps

Artificial Intelligence    |    Intermediate
  • 13 videos | 35m 33s
  • Includes Assessment
  • Earns a Badge
Rating 4.4 of 17 users Rating 4.4 of 17 users (17)
The term MLOps is a combination of machine learning (ML) and DevOps. Used across several industries, MLOps is a valuable method for developing and testing machine learning and artificial intelligence (AI) solutions. Through this course, learn the basics of MLOps. Explore the elements of XOps, MLOps, and DataOps and their uses. Next, examine the importance of version control in machine learning and learn about version control types and tools. Finally, discover the roles and responsibilities of humans in ML pipeline automation and investigate ethical considerations and best practices for MLOps. By the end of this course, you be able to define MLOps and recognize its uses.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline what xops is and its use cases
    Identify what version control is and its importance in machine learning (ml)
    Differentiate between local, distributed, and centralized version control types
    List version control tools and their uses
    State the definition of mlops, its uses cases, and infrastructure elements
    Recognize the benefits of mlops across industries
  • Identify what dataops is and its uses
    Outline the benefits and use cases of dataops
    Identify the elements of the dataops pipeline
    Recognize the role of humans in mlops and the management of ml pipeline automation
    State the ethical concerns of mlops and best practices for ethical conduct
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 40s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 4m 16s
    After completing this video, you will be able to outline what XOps is and its use cases. FREE ACCESS
  • Locked
    3.  Version Control
    3m 37s
    Upon completion of this video, you will be able to identify what version control is and its importance in machine learning (ML). FREE ACCESS
  • Locked
    4.  Types of Version Control
    2m 19s
    During this video, you will learn how to differentiate between local, distributed, and centralized version control types. FREE ACCESS
  • Locked
    5.  Version Control Tools
    2m 34s
    In this video, we will list version control tools and their uses. FREE ACCESS
  • Locked
    6.  What Is MLOps?
    3m 24s
    After completing this video, you will be able to state the definition of MLOps, its uses cases, and infrastructure elements. FREE ACCESS
  • Locked
    7.  Benefits MLOps
    2m 20s
    Upon completion of this video, you will be able to recognize the benefits of MLOps across industries. FREE ACCESS
  • Locked
    8.  What Is DataOps?
    4m 14s
    In this video, you will identify what DataOps is and its uses. FREE ACCESS
  • Locked
    9.  Benefits and Use Cases of DataOps
    2m 22s
    After completing this video, you will be able to outline the benefits and use cases of DataOps. FREE ACCESS
  • Locked
    10.  DataOps Pipeline Elements
    2m 39s
    During this video, we will identify the elements of the DataOps pipeline. FREE ACCESS
  • Locked
    11.  The Role of Humans in ML Pipeline Automation
    2m 54s
    Upon completion of this video, you will be able to recognize the role of humans in MLOps and the management of ML pipeline automation. FREE ACCESS
  • Locked
    12.  MLOps Ethical Concerns
    3m 39s
    After completing this video, you will be able to state the ethical concerns of MLOps and best practices for ethical conduct. FREE ACCESS
  • Locked
    13.  Course Summary
    36s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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