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AWS Machine Learning – Specialty Certification Preparation

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Training content

42
14
15
COURSE
Beginner
Duration: 10 minutes and 18 seconds
Introduction to AWS Machine Learning – Specialty Certification Preparation
This lesson introduces the AWS Certified Machine Learning - Specialty course which prepares you to take the certification exam.
COURSE
Beginner
Duration: 10 minutes and 55 seconds
Observations on the AWS Machine Learning - Specialty Exam
In this lesson, follow along with AWS certification specialist, Stephen Cole, as he discusses his experience taking the AWS Machine Learning - Specialty Exam.
COURSE
Beginner
Duration: 48 minutes and 23 seconds
Introduction to Machine Learning Concepts
In this lesson, you'll learn about Machine Learning and where it fits within the wider Artificial Intelligence (AI) field.
COURSE
Beginner
Duration: 1 hour and 23 minutes
Module 0 - What is Machine Learning? - Part One
This lesson is the first in a two-part series covering the fundamentals of machine learning.
COURSE
Beginner
Duration: 1 hour and 30 minutes
Module 0 - What is Machine Learning? - Part Two
This lesson is part two of the module on machine learning and covers unsupervised learning, the theoretical basis for machine learning, model and linear regression, the semantic gap, and how we approximate the truth.
EXAM
Duration: Up to 35 minutes
Knowledge Check: Practical Machine Learning - Module 0
Knowledge Check: Practical Machine Learning - Module 0
COURSE
Intermediate
Duration: 1 hour and 26 minutes
Working with Distributed Machine Learning
This lesson covers Distributed Machine Learning, Apache Spark, Amazon Elastic Map Reduce, Spark MLib, and AWS Glue.
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Specifically designed to help you prepare for the AWS Machine Learning - Specialty Certification, this preview course provides interactive content comprised of hands-on labs and video courses. This training content has been carefully created to help you study for this AWS certification. 

Learning Objectives

The aim of the certification is to validate your knowledge across a number of different key areas, which have been defined by AWS as being able to:

  • Select and justify the appropriate ML approach for a given business problem.
  • Identify appropriate AWS services to implement ML solutions.
  • Design and implement scalable, cost-optimized, reliable, and secure ML solutions.

As a means of demonstrating this knowledge, you will be tested across six different domains, with each domain contributing to a total percentage of your overall score. These domains are broken down as:

  • Domain 1: Data Engineering 20% 
  • Domain 2: Exploratory Data Analysis 24% 
  • Domain 3: Modelling 36% 
  • Domain 4: Machine Learning Implementation and Operations 20% 

Intended Audience 

This course is suitable for those wanting to pass the AWS Machine Learning - Specialty Certification Exam.

Prerequisites

This is one of the four specialty level certifications available with AWS and it's guided to those who already have experience with AWS, and ideally have already passed an Associate level Exam providing some foundation knowledge of AWS. In addition to this, it is recommended you have experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud, but these are not prerequisites in taking this certification. 

Feedback

We welcome all feedback and suggestions - please contact us at support@cloudacademy.com if you are unsure about where to start or if you would like help getting started. 

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About the Author

Avatar
Stephen Cole, opens in a new tab
AWS Certification Specialist
Students
34,007
Courses
20
Learning paths
12

Stephen is the AWS Certification Specialist at Cloud Academy. His content focuses heavily on topics related to certification on Amazon Web Services technologies. He loves teaching and believes that there are no shortcuts to certification but it is possible to find the right path and course of study.

Stephen has worked in IT for over 25 years in roles ranging from tech support to systems engineering. At one point, he taught computer network technology at a community college in Washington state.

Before coming to Cloud Academy, Stephen worked as a trainer and curriculum developer at AWS and brings a wealth of knowledge and experience in cloud technologies.

In his spare time, Stephen enjoys reading, sudoku, gaming, and modern square dancing.

Covered Topics

Identity and Access Management
Machine Learning
Security
Storage
Analytics
Management
Artificial Intelligence
Amazon Web Services
Security for AWS
Artificial Intelligence for AWS
Storage for AWS
Analytics for AWS
Management for AWS
AWS Glue
Amazon SageMaker
Amazon Rekognition
AWS Identity and Access Management (IAM)
Amazon Lex