This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
Overview
Syllabus
- Introduction
- Course introduction
- AI Foundations
- Introduction
- Why AI
- AI/ML architecture on Google Cloud
- Google Cloud infrastructure
- Data and AI products
- ML model categories
- BigQuery ML
- Lab introduction
- Predicting Visitor Purchases with BigQuery ML
- Summary
- Quiz
- Reading
- AI Development Options
- Introduction
- AI developement options
- Pre-trained APIs
- Vertex AI
- AutoML
- Custom training
- Lab introduction
- Entity and Sentiment Analysis with the Natural Language API
- Summary
- Quiz
- Reading
- AI Development Workflow
- Introduction
- ML workflow
- Data preparation
- Model development
- Model serving
- MLOps and workflow automation
- Lab introduction
- How a machine learns
- Vertex AI: Predicting Loan Risk with AutoML
- Summary
- Quiz
- Reading
- Generative AI
- Introduction
- Generative AI and workflow
- Gemini multimodal
- Prompt design
- Model tuning
- Model Garden
- AI solutions
- Lab introduction
- Get Started with Vertex AI Studio
- Summary
- Quiz
- Reading
- Summary
- Course summary
- Reading
- Your Next Steps
- Course Badge
Tags
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