Exam Topics
As for the MLS-C01 certification test, there are 4 domains that are presented in the exam content. All in all, the topics you need to focus on when preparing for this test are highlighted below:
- Modeling
This is the most prominent part of this exam with a weightage of 36%. This means that it is impossible to get the passing score if you have not mastered this topic. It covers the following sections, including framing business problems as machine learning problems and training machine learning model. In addition, the test takers need to be ready to demonstrate their competence in selecting an appropriate model for specific machine learning problems. They have to possess the ability to perform hyperparameter optimization as well as perform the task of evaluating machine learning models.
- Exploratory Data Analysis
The second subject area covers about 24% of the total weightage and requires that the learners know about data for machine learning. They should know more about machine modeling concepts as well. The questions in this section demand that the candidates possess the skills in preparing data & sanitizing that particular data for modeling. Other items seek to verify their expertise in performing feature engineering. Last but not least, the applicants should demonstrate their understanding of how to perform visualization and canalization of data for machine learning.
- Data Engineering
This domain makes up about 20% of the total questions in the entire exam content. It measures the test takers’ ability to accomplish the technical tasks such as creating machine and learning data repositories. Another section that is included in this topic is implementing & identifying the data ingestion solution. Besides that, the students are also required to demonstrate their skills in implementing and identifying data transformation solutions.
- Machine Learning Implementation and Operations
This is the last objective of the certification exam. It mainly includes the concepts of machine learning services as well as implementation. It carries about 20% weightage in the test. One of the most prominent sections covered within this domain is building machine learning solutions for availability, fault tolerance, resiliency, and performance. It also evaluates the candidates’ knowledge and skills in implementing and recommending the correct machine learning services particularly for a given problem. In addition, the examinees should be ready to demonstrate that they know about applying basic Amazon Web Services (AWS) security practices to specific machine learning solutions. Also, this part requires that the IT pros attempting this test make evident that they have the skills and knowledge required to deploy and operationalize machine learning solutions.
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Understanding functional and technical aspects of AWS Certified Machine Learning - Specialty Modeling
The following will be discussed in AMAZON MLS-C01 exam dumps:
- Select the appropriate model(s) for a given machine learning problem
- Perform hyperparameter optimization
- Evaluate machine learning models
- Frame business problems as machine learning problems
- Train machine learning models
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Target Audience
The Amazon MLS-C01 exam is targeted at those individuals who are tasked with performing the data science or development role. It provides that the candidates can design, deploy, implement, and maintain ML or machine learning solutions for given business problems.
Certification Path
There is no prerequisite for AWS Certified Machine Learning Specialty exam.
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