Machine Learning in AWS: Machine Learning in AWS is the application of artificial intelligence algorithms and models to analyze and interpret data, make predictions, and automate decision-making processes. It is measured in this test to assess candidates' ability to leverage AWS machine learning services and tools in order to develop and deploy intelligent applications and solutions.
Data Science: Data Science involves the extraction of valuable insights from large datasets using statistical and mathematical techniques. Measuring this skill in the test helps assess candidates' proficiency in data manipulation, exploratory data analysis, and creating predictive models to derive actionable business insights.
Data Analysis: Data Analysis is the process of inspecting, cleaning, transforming, and modeling data to uncover useful information, draw conclusions, and support decision-making. It is included in this test to evaluate candidates' ability to analyze and interpret data sets using various statistical and visualization techniques, enabling data-driven decision-making.
Kubernetes: Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. Assessing this skill in the test helps gauge candidates' proficiency in deploying, managing, and scaling applications using Kubernetes in an AWS cloud environment.
AWS DevOps: AWS DevOps refers to the practice of using AWS cloud services and DevOps principles and practices to streamline and automate the software development and deployment processes. Measuring this skill in the test helps evaluate candidates' knowledge and experience in implementing continuous integration, continuous delivery, infrastructure automation, and monitoring using AWS services and tools.