Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Google AI Studio
- Overview of Google AI Studio and its capabilities
- Setting up a workspace and exploring the interface
- Understanding AI project workflows in Google AI Studio
Data Preparation and Management
- Importing and preprocessing datasets
- Exploring data visualization tools
- Ensuring data quality for AI projects
Model Training and Optimization
- Using AutoML for quick model development
- Custom model training with TensorFlow and PyTorch
- Hyperparameter tuning and performance optimization
Model Deployment and Scaling
- Deploying models as REST APIs
- Integrating models with Google Cloud infrastructure
- Scaling AI services for production use
Leveraging Advanced Features
- Implementing Explainable AI (XAI) practices
- Utilizing Google AI APIs for vision, language, and more
- Exploring pre-trained models and transfer learning
Monitoring and Troubleshooting
- Monitoring deployed models for performance
- Analyzing model predictions and feedback
- Troubleshooting common issues in AI workflows
Real-World Applications
- Case studies of AI solutions powered by Google AI Studio
- Building a complete AI project from start to finish
Summary and Next Steps
Requirements
- Strong understanding of machine learning concepts and frameworks
- Experience with Python programming
- Familiarity with Google Cloud services is recommended
Audience
- AI developers
- Machine learning engineers
- Data scientists
21 Hours
