AWS Certified Machine Learning Specialty Exam Study Guide [MLS-C01]

AWS Certified Machine Learning Specialty Study Exam Guide CLF-C01

Preparing for the AWS Certified Machine Learning Specialty exam? Don’t know where to start? This post is the AWS Certified Machine Learning Certificate Study Guide (with links to each objective in the exam domain).

I have curated a detailed list of articles from AWS documentation and other blogs for each objective of the AWS Certified Machine Learning (MLS-C01) exam. Please share the post within your circles so it helps them to prepare for the exam.

AWS Certified Machine Learning Online Course

AWS Certified Machine Learning Practice Test

AWS Certified Machine Learning Preparation

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Data Engineering - 20%

Create Data Repositories for Machine Learning

Identify and Implement a Data-ingestion Solution

Identify and Implement a Data-transformation Solution

Exploratory Data Analysis - 24%

Sanitize and Prepare Data for Modeling

Perform Feature Engineering

Analyze and Visualize Data for Machine Learning

aws certified machine learning

Amazon link (affiliate)

Modeling - 36%

Frame Business Problems as Machine Learning Problems

Select the Appropriate Model(s) for a Given Machine Learning Problem

Train Machine Learning Models

Perform Hyperparameter Optimization

Evaluate Machine Learning Models

Machine Learning Implementation and Operations - 20%

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

Apply Basic AWS Security Practices to Machine Learning Solutions

Deploy and Operationalize Machine Learning Solutions

This brings us to the end of the AWS Certified Machine Learning – Specialty [MLS-C01] Exam Preparation Study Guide.

What do you think? Let me know in the comments section if I have missed out on anything. Also, I love to hear from you about how your preparation is going on!

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