GCP - Google Cloud Professional Machine Learning Engineer

About this course

Become a job-ready Google Cloud Professional Machine Learning Engineer by mastering end-to-end Machine Learning, Generative AI, RAG architectures, and Agent development on Google Cloud Platform. This course is fully hands-on and covers the complete ML lifecycle — from SQL-based modeling with BigQuery ML to advanced AI systems using Vertex AI, Gemini models, and the Agent Development Kit (ADK).

You will start by building production-ready Machine Learning models using BigQuery ML, including regression, boosted trees, classification, recommendation systems, anomaly detection with autoencoders, time-series forecasting, and advanced feature engineering. From there, you will explore Vertex AI Model Garden to create text generation workflows, multimodal AI applications, image generation pipelines, and real-world AI solutions.

The course goes far beyond traditional ML by teaching you how to design intelligent systems powered by Generative AI. You will build complete projects using the Document AI API for large-scale document processing, develop AutoML pipelines for tabular, text, image, and forecasting workloads, and implement enterprise-grade AI agents using Google’s Agent Development Kit.

Inside the Agent Development section, you will create starter agents, tool-enabled agents, multi-agent systems, stateful workflows, persistent storage, callbacks, sequential and parallel agent architectures, and deploy production-ready agents to Vertex AI Agent Engine and Cloud Run.

You will also design modern enterprise AI architectures including:

• Retrieval-Augmented Generation (RAG) systems using Vertex AI RAG EngineVector Search pipelines with embeddings, indexing, and querying
• Vertex AI Search implementations for enterprise search use cases

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