In addition, the certification exam evaluates a candidate’s ability to implement strategies for deploying machine learning models. Finally, candidates are assessed on their ability to build monitoring solutions to detect data drift. Individuals who pass the certification exam can be expected to perform advanced machine learning engineering tasks using Databricks Machine Learning.
Google Cloud Professional Machine Learning Engineer
A professional machine learning engineer builds, evaluates, produces, and optimizes machine learning models using Google Cloud technologies and has knowledge of proven models and techniques, according to Google Cloud. The Google Cloud Professional Machine Learning Engineer certification ensures a machine learning engineer can handle large, complex datasets and create repeatable, reusable code; consider responsible AI and fairness throughout the machine learning model development process; and collaborate closely with other job roles to ensure long-term success of machine learning-based applications.
The Google Cloud Professional certified machine learning engineer also must have strong programming skills and experience with data platforms and distributed data processing tools, Google Cloud says. This professional is also expected to be proficient in the areas of model architecture, data and machine learning pipeline creation, and metrics interpretation. By training, retraining, deploying, scheduling, monitoring, and improving models, the machine learning engineer designs and creates scalable solutions.