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Duration 14 hours
Course Outline
Introduction to Google Vertex AI
- An overview of Google Vertex AI and its core capabilities
- Key features that benefit AI model development
- A detailed look at the Vertex AI workflow
Setting Up Google Vertex AI
- Creating a Google Cloud account and initializing Vertex AI
- Configuring the environment and managing associated resources
- Exploring the Vertex AI interface and its toolset
Building AI Models with Vertex AI
- Data preparation and preprocessing methodologies
- Training custom AI models through Vertex AI
- Assessing model performance and accuracy metrics
Deployment and Management of AI Models
- Strategies for deploying AI models on the Google Cloud Platform
- Monitoring and maintaining models in production
- Scaling AI solutions to handle varying demand levels
Advanced Features and Performance Optimization
- Leveraging Vertex AI’s advanced tools and services
- Tuning model performance for specific use cases
- Applying best practices for robust model development and deployment
Real-World Applications and Case Studies
- Examining Vertex AI applications across various industries
- Analyzing case studies of successful AI implementations
- Discussing common challenges and key lessons learned
Summary and Future Directions
Requirements
- Foundational knowledge of AI and machine learning principles
- Proficiency in programming languages (Python is recommended)
- Experience working with cloud platforms (Google Cloud Platform preferred)
Target Audience
- Software Developers
- Data Scientists
- Technology Professionals
Testimonials (1)
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