Cloud Computing and MLOps: Introduction to MLOps
Artificial Intelligence
| Intermediate
- 13 videos | 35m 33s
- Includes Assessment
- Earns a Badge
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
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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
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40sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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4m 16sAfter completing this video, you will be able to outline what XOps is and its use cases. FREE ACCESS
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3. Version Control3m 37sUpon completion of this video, you will be able to identify what version control is and its importance in machine learning (ML). FREE ACCESS
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4. Types of Version Control2m 19sDuring this video, you will learn how to differentiate between local, distributed, and centralized version control types. FREE ACCESS
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5. Version Control Tools2m 34sIn this video, we will list version control tools and their uses. FREE ACCESS
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6. What Is MLOps?3m 24sAfter completing this video, you will be able to state the definition of MLOps, its uses cases, and infrastructure elements. FREE ACCESS
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7. Benefits MLOps2m 20sUpon completion of this video, you will be able to recognize the benefits of MLOps across industries. FREE ACCESS
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8. What Is DataOps?4m 14sIn this video, you will identify what DataOps is and its uses. FREE ACCESS
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9. Benefits and Use Cases of DataOps2m 22sAfter completing this video, you will be able to outline the benefits and use cases of DataOps. FREE ACCESS
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10. DataOps Pipeline Elements2m 39sDuring this video, we will identify the elements of the DataOps pipeline. FREE ACCESS
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11. The Role of Humans in ML Pipeline Automation2m 54sUpon 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
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12. MLOps Ethical Concerns3m 39sAfter completing this video, you will be able to state the ethical concerns of MLOps and best practices for ethical conduct. FREE ACCESS
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13. Course Summary36sIn 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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