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Machine Learning Implementation and Operations in AWS
  • Level Foundation
  • Duration 6 hours
  • Course by Whizlabs
  • Offered by

About

Machine Learning Implementation Operations in AWS is the fifth Course in the AWS Certified Machine Learning Specialty specialization. The course has a major focus on designing and implementing machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 1:00-1:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners. Module 1: Machine Learning Implementation Operations in AWS-Part 1 Module 2: Machine Learning Implementation Operations in AWS-Part 2 Minimum two year of hands-on experience in architecting, building or running ML/deep learning workloads on the AWS Cloud. By the end of this course, Learners will be able to : -Design machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance -Implement appropriate machine learning services and features for a given problem -Develop machine learning solutions with lab

Modules

Build machine learning solutions

    • 7 Videos
    • 3 Readings
    • 1 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Machine Learning Implementation andOperations in AWS-Part 1 Knowledge Test
  • Week 1 Assessment

1 Discussions

  • Meet and Greet

7 Videos

  • Introduction- Machine Learning Implementation and Operations
  • Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance
  • Recommend and implement the appropriate machine learning services and features for a given problem-Part 1
  • Recommend and implement the appropriate machine learning services and features for a given problem-Part 2
  • Amazon Fraud Detector
  • Amazon Fraud Detector - Build, Train and Deploy the Fraud Detector Model
  • Amazon Fraud Detector - Generate Fraud Detector

3 Readings

  • Course Outline
  • Welcome to the Course
  • Machine Learning Implementation and Operations in AWS-Part 1 Overview

AWS security practices to ML solutions

    • 9 Videos
    • 3 Readings
    • 3 Discussion
    • 2 Assignment
Show info about module content

2 Assignment

  • Week 2 Assessment
  • Overall Course Assessment Quiz

3 Discussions

  • Hands-On Activity-Build a sample chatbot using Amazon Lex
  • Hands-on Activity-Chatbot using Amazon Lex and store bot response in DynamoDB
  • Amazon Lex chatbot using 3rd party API

9 Videos

  • Apply basic AWS security practices to machine learning solutions
  • Deploy and operationalize machine learning solutions with lab-Part 1
  • Deploy and operationalize machine learning solutions with lab-Part 2
  • AWS IoT Greengrass
  • Amazon Connect
  • Amazon Connect - Demo
  • Exam tips
  • Summary of the course
  • Exam day tips

3 Readings

  • Machine Learning Implementation and Operations in AWS-Part 2 Overview
  • Key Takeaways of the Course
  • Course Conclusion

Auto Summary

This course on Machine Learning Implementation and Operations in AWS, taught by Coursera, delves into designing and implementing ML solutions with a focus on performance, scalability, and fault tolerance. Divided into two modules, it offers 1-1.5 hours of video lectures, quizzes, and hands-on labs. Ideal for those with two years of AWS ML experience, it aims to equip learners to design and implement robust ML solutions. The course is part of the AWS Certified Machine Learning Specialty and is suited for foundational learners.

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Whizlabs Instructor