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Cloud Machine Learning Engineering and MLOps
  • Level Professional
  • المدة 12 ساعات hours
  • الطبع بواسطة Duke University
  • Offered by

عن

Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone. Finally, you will dive into emerging topics in Machine Learning including MLOps, Edge Machine Learning and AI APIs. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a Flask web application that serves out Machine Learning predictions.

الوحدات

Welcome to the the Course!

    • 4 Videos
    • 2 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Introductions

4 Videos

  • Instructor Introduction
  • Course Introduction
  • Lab Onboarding
  • Course 4 Project Overview

2 Readings

  • Specialization Project Roadmap: Course 4
  • Course Structure and Discussion Etiquette

What is Machine Learning Engineering?

    • 3 Videos
    • 2 Readings
Show info about module content

3 Videos

  • Introduction to Machine Learning Engineering
  • Machine Learning Engineering Overview
  • Machine Learning Engineering Architecture

2 Readings

  • Jupyter Notebook Workflow for Machine Learning
  • K-Means Clustering Sample Dataset

Build Machine Learning Microservices

    • 3 Videos
    • 1 Discussion
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1 Discussions

  • Microservices in MLOps

3 Videos

  • Introduction to Machine Learning Microservices
  • Machine Learning Microservices Overview
  • Monolithic versus Microservice

Continuous Delivery for Machine Learning

    • 5 Videos
    • 1 Discussion
    • 1 Lab
Show info about module content

1 Discussions

  • PaaS (Platform as a Service) and MLOPs

1 Labs

  • Flask Machine Learning Microservice

5 Videos

  • Introduction to Continuous Delivery for Machine Learning
  • Continuous Delivery for Machine Learning Overview
  • What is Data Drift?
  • Continuously Deploy Flask ML Application
  • AWS App Runner: High-Level PaaS Continuous Delivery

Applied Practice

    • 1 Readings
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1 Readings

  • High Level MLOps Continuous Deployment

Graded Assignment

    • 1 Assignment
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1 Assignment

  • Quiz

What is AutoML?

    • 7 Videos
    • 1 Readings
    • 1 Discussion
Show info about module content

1 Discussions

  • Impact of AutoML?

7 Videos

  • Introduction to AutoML
  • What is AutoML?
  • AutoML Computer Vision
  • Introduction to No Code/Low Code
  • No Code/Low Code AutoML: Part 1
  • No Code/Low Code AutoML: Part 2
  • Apple Create ML AutoML

1 Readings

  • Managed Machine Learning Systems

Ludwig AutoML

    • 4 Videos
    • 1 Discussion
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1 Discussions

  • Open Source AutoML

4 Videos

  • Introduction to Ludwig AutoML
  • What is Ludwig AutoML?
  • Ludwig AutoML Deep Dive
  • Ludwig AutoML By Example

Cloud AutoML

    • 10 Videos
    • 1 Discussion
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1 Discussions

  • ML Studio Products

10 Videos

  • Introduction to Cloud AutoML
  • What is Cloud AutoML?
  • Cloud AutoML Deep Dive
  • Guest Speaker: Alfredo Deza
  • Introduction to Azure Machine Learning Studio
  • Create a Dataset in Azure Machine Learning Studio
  • Automated ML Run in Azure Machine Learning Studio
  • Experiments in Azure Machine Learning Studio
  • Deploy a Module in Azure Machine Learning Studio
  • Test Endpoints in Azure Machine Learning Studio

Applied Practice

    • 1 Readings
Show info about module content

1 Readings

  • Use Apple's AutoML Computer Vision

Graded Assignment

    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz

What is MLOps?

    • 3 Videos
    • 1 Discussion
    • 1 Lab
Show info about module content

1 Discussions

  • Why MLOps?

1 Labs

  • Pickle an ML Model

3 Videos

  • Introduction to MLOps
  • What is MLOps?
  • MLOps Deep Dive

Using Edge Machine Learning

    • 6 Videos
    • 1 Discussion
Show info about module content

1 Discussions

  • Edge Machine Learning

6 Videos

  • Introduction to Edge Machine Learning
  • What is Edge Machine Learning?
  • Edge Machine Learning Vision in Action
  • Hardware Inference Model Solutions in Edge Machine Learning
  • Edge Machine Learning in Google
  • Edge Machine Learning in AWS

Using AI APIs

    • 10 Videos
    • 1 Discussion
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1 Discussions

  • No Code and Low Code Solutions

10 Videos

  • Introduction to AI APIs
  • How to Use AI APIs?
  • Core Components of a Cloud Application
  • AWS Comprehend for Natural Language Processing
  • AWS Rekognition for Computer Vision
  • GCP AutoML for Natural Language Processing
  • GCP AutoML for Computer Vision
  • Azure AutoML for AI Predictions
  • Azure AutoML for Computer Vision
  • Core Components of a Cloud Application Recap

Building a Professional Web Service

    • 3 Videos
    • 1 Discussion
Show info about module content

1 Discussions

  • Standards of Excellence in Software Engineering

3 Videos

  • Steps to Developing an API
  • Flask Machine Learning Backend
  • Checklist for Building Professional Web Services

Applied Practice

    • 1 Readings
Show info about module content

1 Readings

  • Deep Dive: Use a Low Code or No Code Cloud AI API to Solve a Problem

Graded Assignment

    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz

Putting it all Together: Final Course Project

    • 2 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Interactive Llamafile Sandbox

2 Readings

  • Deploy a Flask Machine Learning Model That You Didn't Build
  • Next Steps

Auto Summary

Join the "Cloud Machine Learning Engineering and MLOps" course on Coursera, designed for IT & Computer Science enthusiasts. Enhance your skills in Machine Learning Engineering, AutoML, MLOps, and Edge Machine Learning through practical applications and best practices. Ideal for beginners and intermediates with Linux and Python knowledge, this professional-level course spans 720 minutes. Subscription options include Starter and Professional. Perfect for those looking to integrate cloud computing with data science and engineering.

Noah Gift
Instructor

Noah Gift