
Google Cloud Professional Machine Learning Engineer
Description
Google Cloud Professional Machine Learning Engineer
Course Description
This course prepares learners for the Google Cloud Professional Machine Learning Engineer certification by focusing on the practical skills needed to design, build, and deploy machine learning models using Google Cloud Platform (GCP). The course covers the full ML lifecycle—from data preparation and modeling to operationalization and monitoring—while emphasizing security, compliance, and responsible AI practices.
What You’ll Learn
Design ML solutions using GCP tools like Vertex AI, BigQuery, and AutoML
Prepare and process structured and unstructured data for training and evaluation
Train, test, deploy, and monitor ML models in production environments
Apply responsible AI principles including model fairness, explainability, and data privacy
Requirements
Solid understanding of Python and basic machine learning concepts
Familiarity with TensorFlow or scikit-learn is helpful
Experience working with cloud services, especially Google Cloud, is recommended
Access to a Google Cloud account for hands-on labs and exercises
Who This Course Is For
Individuals preparing for the Google Cloud Professional Machine Learning Engineer certification
Data scientists, ML engineers, and AI specialists working on cloud-based solutions
Software engineers and developers integrating ML models into applications
Professionals seeking to validate their ability to build scalable, production-ready ML pipelines on GCP
This course aligns with Google’s exam guide and includes real-world case studies, best practices, and hands-on labs that simulate tasks performed by ML engineers in production settings.
Who this course is for:
- Individuals preparing for the Google Cloud Professional Machine Learning Engineer certification exam Data scientists and machine learning engineers working with cloud-based ML solutions Software developers integrating machine learning into applications and services AI practitioners looking to operationalize and scale models using Google Cloud tools
Instructor
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