Angielski
LEARN VERTEX AI Implement Enterprise AI on Google Cloud
This book is aimed at technology professionals, data engineers, and students who want to master the use of Vertex AI for creating, automating, and governing artificial intelligence projects in corporate Google Cloud environments.
Learn how to structure machine learning pipelines, integrate data, automate deployment and versioning processes, monitor performance, and implement MLOps and DataOps practices with security, scalability, and compliance. Explore practical integrations with BigQuery, Dataflow, Pub/Sub, Cloud Storage, as well as leading frameworks such as TensorFlow, PyTorch, and scikit-learn. Develop skills in multi-cloud deployment, model tuning, cost control, CI/CD automation, and complete governance of the data and model lifecycle.
• Professional setup of Vertex AI on Google Cloud
• Building automated and scalable machine learning pipelines
• Advanced integration with BigQuery, Dataflow, Pub/Sub, and Cloud Storage
• Deployment, versioning, and monitoring of production models
• Orchestration with TensorFlow, PyTorch, scikit-learn, AutoML, and containers
• CI/CD automation, performance tuning, cost control
• Implementation of Feature Store, Model Registry, and access policies
• Governance, auditing, compliance, and data security in AI
• MLOps, DataOps strategies, and multi-cloud integration
• Real-world applications, certification preparation, and critical projects
Master Vertex AI and become a reference in corporate AI, delivering scalable, auditable projects aligned with global market demands.
vertex ai, google cloud, machine learning, nvidia, pipelines, automation, bigquery, dataflow, pub/sub, cloud storage, ci/cd, mlops, automl, tensorflow, pytorch, feature store, model registry, dataops, model deployment, orchestration, monitoring, governance, data security
