Getting Started with MLOps
MLOps
| Beginner
- 11 videos | 1h 27m 21s
- Includes Assessment
- Earns a Badge
MLOps is the integration of machine learning (ML) with DevOps, focusing on streamlining the end-to-end machine learning life cycle. It emphasizes collaboration, automation, and reproducibility to deliver reliable and scalable machine learning solutions. By implementing MLOps practices, organizations can efficiently manage and govern their machine learning workflows, leading to faster development cycles, better model performance, and enhanced collaboration among data scientists and engineers. In this course, you will delve into the theoretical aspects of MLOps and understand what sets it apart from traditional software development. You will explore the factors that affect ML models in production and gain insights into the challenges and considerations of deploying machine learning solutions. Next, you will see how the Machine Learning Canvas can help you understand the components of ML development. You will then explore the end-to-end machine learning workflow, covering stages from data preparation to model deployment. Finally, you will look at the different stages in MLOps maturity in your organization, levels 0, 1, and 2. You will learn how organizations evolve in their MLOps journey and the key characteristics of each maturity level.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Provide an overview of devops and mlops
Outline how mlops works
Identify the features of mlops
Recognize the challenges of mlops
Outline the use of the machine learning canvas -
Outline the ml workflow
Recognize ml architectural patterns
Outline level 0 of ml pipelines
Outline level 1 and 2 of ml pipelines
Summarize the key concepts covered in this course
IN THIS COURSE
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1m 59sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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12m 3sAfter completing this video, you will be able to provide an overview of DevOps and MLOps. FREE ACCESS
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3. What's Different About MLOps?10m 24sUpon completion of this video, you will be able to outline how MLOps works. FREE ACCESS
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4. Factors Affecting Machine Learning (ML) Models in Production8m 22sAfter completing this video, you will be able to identify the features of MLOps. FREE ACCESS
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5. Solving Machine Learning Problems4m 19sUpon completion of this video, you will be able to recognize the challenges of MLOps. FREE ACCESS
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6. The Machine Learning Canvas12m 53sAfter completing this video, you will be able to outline the use of the machine learning canvas. FREE ACCESS
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7. End-to-end Machine Learning Workflow6m 59sUpon completion of this video, you will be able to outline the ML workflow. FREE ACCESS
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8. ML Workflow Architectural Patterns11m 20sAfter completing this video, you will be able to recognize ML architectural patterns. FREE ACCESS
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9. Stages in MLOps Maturity Level 05m 58sUpon completion of this video, you will be able to outline level 0 of ML pipelines. FREE ACCESS
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10. Stages in MLOps Maturity Level 1 and 29m 38sAfter completing this video, you will be able to outline level 1 and 2 of ML pipelines. FREE ACCESS
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11. Course Summary3m 27sIn 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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