Google Cloud Professional Machine Learning Engineer

About this course

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 AutoMLPrepare 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 ForIndividuals 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.<

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