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Google Vertex AI is a cloud-based platform that allows developers and data scientists to build, train, and deploy machine learning models quickly. It provides integrated tools for data preparation, model training, evaluation, and deployment, making AI development simpler and more accessible.
This certification prepares individuals to manage end-to-end AI projects, including data handling, model building, and production deployment. Candidates learn to streamline AI workflows, implement scalable models, and apply machine learning techniques effectively in real-world business and technical scenarios.
This exam is ideal for:
Domain 1 - Introduction to Google Vertex AI
Domain 2 - Data Preparation and Management
Domain 3 - Model Training and Evaluation
Domain 4 - Deployment and Serving
Domain 5 - Pipelines and Workflow Automation
Domain 6 - MLOps and Model Monitoring
Domain 7 - Using Pre-Built AI Services
Domain 8 - Security and Best Practices
Industry-endorsed certificates to strengthen your career profile.
Start learning immediately with digital materials, no delays.
Practice until you’re fully confident, at no additional charge.
Study anytime, anywhere, on laptop, tablet, or smartphone.
Courses and practice exams developed by qualified professionals.
Support available round the clock whenever you need help.
Easy-to-follow content with practice exams and assessments.
Join a global community of professionals advancing their skills.
Yes, it covers pipelines and automated ML workflows.
Data scientists, ML engineers, developers, cloud architects, and AI enthusiasts.
Basic knowledge helps, but beginners can also start with fundamental ML concepts.
Yes, best practices for cost optimization are covered.
Yes, Vertex AI supports Vision, Language, Translation, and AutoML APIs.
Yes, including model monitoring, versioning, retraining, and governance.
Yes, understanding Google Cloud Platform improves application of Vertex AI.
ML Engineer, Data Scientist, AI Developer, Cloud AI Specialist, Research Engineer.
Finance, healthcare, e-commerce, manufacturing, research, and tech startups.
Yes, it covers basic to advanced AI workflows and Google Cloud integration.
Yes, from dataset preparation to model performance metrics.
Yes, including real-time endpoints, batch predictions, and scaling.
Yes, familiarity with Python or similar languages is recommended.
It enhances employability in AI/ML roles, cloud computing, and research positions.
Yes, candidates learn to deploy scalable and practical AI solutions for businesses.