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- المدة
- الطبع بواسطة Statistics.com
- Total students 596 enrolled
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Offered by
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Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how to automate your pipeline's functions and continuously optimize its performance, which is why we developed this course: MLOps2 (AWS): Data Pipeline Automation & Optimization using Amazon Web Services. In this course you will learn how to set up automated monitoring of your data pipeline for prediction. Data drift, model drift and feedback loops can impair model performance and model stability, and you will learn how to monitor for those phenomena. You will also learn about setting triggers and alarms, so that operators can deal with problems with model instability. You will also cover ethical issues in machine learning and the risks they pose, and learn about the "Responsible Data Science" framework.
What you will learn
You will learn how to set up automated monitoring of your data pipeline for prediction and get hands on experience with topics like data pipelines, drift and feedback loops, model stability, triggers & alarms, model security, responsible AI and much more.
But most importantly, by the end of this course, you will know…
- How to meet the differing requirements of model training versus model inference in your pipeline
- How to check for model drift, data drift, and feedback loops
- How to apply the principles of Continuous Integration (CI), Continuous Delivery (CDE) and Continuous Deployment (CD)
Skills you learn
Syllabus
Week 1 – Drift and Feedback Loops
- Module 1: Training Versus Inference Pipelines
- Module 2: Drift & Feedback Loops
Week 2 – Triggers, Alarms & Model Stability
- Module 3: Triggers & Alarms
- Module 4: Model Stability
Week 3 – CI/CD (Continuous Integration & Continuous Deployment/Delivery)
- Module 5: CI/CD
Week 4 – Model Security and Responsible AI
- Module 6: Responsible AI
Auto Summary
MLOps2 (AWS): Data Pipeline Automation & Optimization using Amazon Web Services is an IT & Computer Science course offered by edX. Focused on overcoming deployment challenges in data science projects, it teaches automation and continuous optimization of data pipelines on AWS. Perfect for beginners, the course offers Starter and Professional subscription options.

Peter Bruce

Evan Wimpey

Vic Diloreto

Laura Lancheros

Greg Carmean

Kuber Deokar

Janet Dobbins