Amazon MLS-C01 Exam Syllabus

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Before starting your MLS-C01 exam preparation, it is recommended to review the complete Amazon AWS Certified Machine Learning - Specialty exam syllabus and carefully go through the exam objectives listed below. Once you understand the exam structure and objectives, you should practice using our free MLS-C01 questions. We also provide premium MLS-C01 practice test, fully updated according to the latest exam objectives, to help you accurately assess your preparedness for the actual exam.

Amazon MLS-C01 Exam Objectives

Section	Weight	Objectives
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.
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.
Official Information		https://d1.awsstatic.com/training-and-certification/docs-ml/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide%20(1).pdf

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