So you’re thinking about taking the AWS Certified Machine Learning – Specialty exam? In this article, I’ll provide all of the topics covered in this exam along with courses and practice exams so that you can pass this exam quickly and efficiently.

The AWS Certified Machine Learning – Specialty is likely the most popular and practical certification for machine learning and data science. This exam tests you on the following 4 domains:

  • Data Engineering
  • Exploratory Data Analysis
  • Modeling
  • Machine Learning Implementation and Operations

Additionally, about half of the questions are focused solely on machine learning concepts and not just AWS’s products.

Here are the specific concepts that the exam tests you on:

AWS Certified Machine Learning Specialty

You’ll want to know what each of these topics are and how they are used in order to pass this exam.

And as you can guess, it’s definitely recommended that you have experience with machine learning concepts before attempting this exam.

Resources

Here are some resources that you can use to study for the certification:

You can download the exam guide and sample questions on the web page for this certification.

AWS Certified Machine Learning – Specialty (Main Page)

Here’s a helpful AWS course on Udemy and it provides explanations about all of the main topics on the exam.

AWS Certified Machine Learning Specialty 2020 – Hands On!

This AWS course on Udemy provides 65 practice exam questions and should help you know what to expect.

AWS Certified Machine Learning Specialty: Full Practice Exam (Udacity)

Why should you consider the AWS Certified Machine Learning – Specialty?

Google Trends is a great way to assess the trends of vendors associated with certifications. For example, AWS has a considerably higher search volume in Google Trends than other cloud companies worldwide and that search volume is growing at a fast rate.

AWS also has the highest market share among all of the cloud platforms.

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Disclaimer: A couple of the links in the description are affiliate links.

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