GCP Machine Learning Engineer Course (Beginner to Advanced, 2025 Edition)

  • Home
  • Learn By Role
  • GCP Machine Learning Engineer Course (Beginner to Advanced, 2025 Edition)

GCP Machine Learning Engineer Course (Beginner to Advanced, 2025 Edition)

Master Machine Learning on Google Cloud Platform with a modern 2025 curriculum. Learn end-to-end ML workflows using Vertex AI, build scalable data pipelines with BigQuery and Dataflow, deploy production-grade ML models, and create Generative AI applications with Gemini and Vertex AI. Includes multiple real-world capstone projects covering MLOps, RAG systems, and AI agent workflows.

  • 7 Phases
  • 20 Lessons
  • 4.4 Hrs
  • Beginner Advanced
Category Cloud computing
GCP Machine Learning Engineer Course (Beginner to Advanced, 2025 Edition)
Learning Path 20 Lessons 4.4 Hrs

Start Phase
  • Machine Learning on Google Cloud – Practical Overview 7

Start Phase
  • Google Cloud Storage for ML Data 23
  • Data Preparation with BigQuery & Dataflow 38
  • Feature Engineering with Vertex AI Feature Store 7

Start Phase
  • Introduction to Vertex AI 3
  • Training and Hyperparameter Tuning in Vertex AI 11
  • Experiment Tracking with Vertex AI Experiments 14

Start Phase
  • Deep Learning VMs with GPUs on GCP 21
  • Image Classification with Vertex AI 5
  • Deploy Hugging Face Models on Vertex AI 7

Start Phase
  • CI/CD for ML Models with Vertex AI Pipelines 17
  • Deploying Models with Vertex AI Endpoints 6
  • Model Monitoring and Drift Detection with Vertex AI 11

Start Phase
  • Using Gemini with Vertex AI via FastAPI (Hands-On) 8
  • Build Vertex AI RAG Agent with Search & Vector Search 33

Start Phase
  • Project 1: Setting Up GCP Project & Service Account 5
  • Project 2A: Build ML Pipeline on Vertex AI with Kubeflow 23
  • Project 2B: Run & Monitor ML Pipeline on Vertex AI 11
  • Project 3: RAG-Powered Intelligent Search Assistant 4
  • Project 4: Agentic AI Workflow with Gemini & Vertex AI 11

Start your GCP Machine Learning Engineer Course (Beginner to Advanced, 2025 Edition) journey

Learn at your own pace. Total estimated time 4.4 hours

Start learning today — completely free

Our mission is to help you learn faster with the best free resources online.