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
- An overview of Google AI Studio’s features and capabilities
- Configuring your workspace and exploring the user interface
- Understanding AI project workflows within Google AI Studio
Data Preparation and Management
- Importing and preprocessing datasets
- Investigating data visualisation tools
- Maintaining data quality for AI initiatives
Model Training and Optimisation
- Utilising AutoML for rapid model development
- Custom model training using TensorFlow and PyTorch
- Hyperparameter tuning and performance enhancement
Model Deployment and Scaling
- Releasing models as REST APIs
- Integrating models with Google Cloud infrastructure
- Scaling AI services for production environments
Utilising Advanced Features
- Implementing Explainable AI (XAI) standards
- Using Google AI APIs for vision, language, and other applications
- Exploring pre-trained models and transfer learning techniques
Monitoring and Troubleshooting
- Tracking the performance of deployed models
- Analysing model predictions and user feedback
- Resolving common issues in AI workflows
Real-World Applications
- Case studies of AI solutions powered by Google AI Studio
- Constructing a complete AI project from inception to completion
Summary and Future Steps
Requirements
- A solid grasp of machine learning theories and frameworks
- Proficiency in Python programming
- Familiarity with Google Cloud services is advised
Target Audience
- AI Developers
- Machine Learning Engineers
- Data Scientists
21 Hours
