Available AWS Certifications
Knowledge and Expertise
High Level Sections
Powerful Machine Learning Platform
Take the Test with Confidence
All Sections Covered
- Create data repositories for machine learning
- Identify and implement data-ingestion and data-transformation solutions
- Sanitize and prepare data for modeling
- Perform feature engineering
- Analyze and visualize data for machine learning
- 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
- 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
Recommended Knowledge
Hands-on Experience
CIO Magazine
Machine learning to remain most in-demand AI skill
- Machine learning today is used for image identification and classification at scale, consumer-driven chatbots, NLP and voice search, lead prediction, and more advanced neural networks, like Goole’s DeepMind network. The applications for and uses of machine learning are just now becoming realized, but employer demand for talent with ML skills has already risen dramatically.
- Over the post three years alone the number of AI-related job postings on Indeed has increased by 119 percent, according to the platform’s latest AI talent report. The machine learning engineer role was cited as the third most in-demand AI job of moment with machine learning ranked as the most in-demand AI skill. With AI projected to create 2.3 million jobs by 2020, according to a Gartner report, I think it’s safe to assume that machine learning will remain an in-demand skill for the foreseeable future.
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