MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning

Monthly Subscription Starting at AED 99 + VAT

Level Awareness
Duration 26 hours
Course by Statistics.com
Total students 761 enrolled
Offered by

About

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 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning. 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

Unlock the secrets to successful data science project deployment with the MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning course. Offered by edX, this course delves into the critical aspects of automating and optimizing data pipelines using Microsoft Azure Machine Learning. Designed for IT and Computer Science enthusiasts, it addresses common pitfalls in deployment and equips learners with the necessary skills to ensure continuous performance enhancement. Guided by expert instructors, this 26-hour course offers a comprehensive curriculum that focuses on practical applications and real-world scenarios. Whether you are new to the field or looking to deepen your knowledge, the course is accessible at an awareness level, making it suitable for a broad audience. Flexible subscription options, including Starter and Professional, provide learners with the opportunity to choose a plan that best fits their needs and goals. Join this engaging and informative course to elevate your data science projects and master the art of pipeline automation and optimization with Microsoft Azure Machine Learning.