AWS Certified Machine Learning Study Guide: Specialty (MLS-C01) Exam

  • 7h
  • Shreyas Subramanian, Stefan Natu
  • Sybex
  • 2021

Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide

As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learning business solutions.

The AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivers hyper-focused, authoritative instruction for anyone considering the pursuit of the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist working within the AWS architecture.

From exam to interview to your first day on the job, this study guide provides the domain-by-domain specific knowledge you need to build, train, tune, and deploy machine learning models with the AWS Cloud. And with the practice exams and assessments, electronic flashcards, and supplementary online resources that accompany this Study Guide, you’ll be prepared for success in every subject area covered by the exam.

You’ll also find:

  • An intuitive and organized layout perfect for anyone taking the exam for the first time or seasoned professionals seeking a refresher on machine learning on the AWS Cloud
  • Authoritative instruction on a widely recognized certification that unlocks countless career opportunities in machine learning and data science
  • Access to the Sybex online learning resources and test bank, with chapter review questions, a full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms

AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam is an indispensable guide for anyone seeking to prepare themselves for success on the AWS Certified Machine Learning Specialty exam or for a job interview in the field of machine learning, or who wishes to improve their skills in the field as they pursue a career in AWS machine learning.

About the Author

Shreyas Subramanian, PhD, is Principal Machine Learning specialist at Amazon Web Services. He has worked with several enterprise companies on business-critical machine learning and optimization problems.

Stefan Natu is Principal Machine Learning Specialist at Alexa AI, prior to which he was a Principal Architect at Amazon Web Services. His professional focus is on financial services, and he helps customers architect ML use cases on AWS with an emphasis on security, enterprise model governance, and operationalizing machine learning models.

In this Book

  • Introduction
  • Assessment Test
  • Answers to Assessment Test
  • AWS AI ML Stack
  • Supporting Services from the AWS Stack
  • Business Understanding
  • Framing a Machine Learning Problem
  • Data Collection
  • Data Preparation
  • Feature Engineering
  • Model Training
  • Model Evaluation
  • Model Deployment and Inference
  • Application Integration
  • Operational Excellence Pillar for ML
  • Security Pillar
  • Reliability Pillar
  • Performance Efficiency Pillar for ML
  • Cost Optimization Pillar for ML
  • Recent Updates in the AWS AI/ML Stack


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