מתווה קורס מפורט
Module 1 - AI Foundations
Topics:
- Why AI?
- AI/ML framework on Google Cloud
- Google Cloud infrastructure
- Data and AI products
- ML model categories
- BigQuery ML
- Lab introduction: BigQuery ML
Objectives:
- Recognize the AI/ML framework on Google Cloud.
- Identify the major components of Google Cloud infrastructure.
- Define the data and ML products on Google Cloud and how they support the data-to-AI lifecycle.
- Build an ML model with BigQueryML to bring data to AI.
Activities:
- Lab: Predicting Visitor Purchases with BigQuery ML
- Quiz
- Reading
Module 2 - AI Development Options
Topics:
- AI development options
- Pre-trained APIs
- Vertex AI
- AutoML
- Custom training
- Lab introduction: Natural Language API
Objectives:
- Define different options to build an ML model on Google Cloud.
- Recognize the primary features and applicable situations of pre-trained APIs, AutoML, and custom training.
- Use the Natural Language API to analyze text.
Activities:
- Lab: Entity and Sentiment Analysis with Natural Language API
- Quiz
- Reading
Module 3 - AI Development Workflow
Topics:
- ML workflow
- Data preparation
- Model development
- Model serving
- MLOps and workflow automation
- Lab introduction: AutoML
- How a machine learns
Objectives:
- Define the workflow of building an ML model.
- Describe MLOps and workflow automation on Google Cloud.
- Build an ML model from end to end by using AutoML on Vertex AI.
Activities:
- Lab: Vertex AI: Predicting Loan Risk with AutoML
- Quiz
- Reading
Module 4 - Generative AI
Topics:
- Generative AI and workflow
- Gemini multimodal
- Prompt design
- Model tuning
- Model Garden
- AI solutions
- Lab introduction: Vertex AI Studio
Objectives:
- Define generative AI and foundation models.
- Use Gemini multimodal with Vertex AI Studio.
- Design efficient prompt and tune models with different methods.
- Recognize the AI solutions and the embedded Gen AI features.
Activities:
- Lab: Getting Started with Vertex AI Studio
- Quiz
- Reading
Module 5 - Course Summary
Topics:
- Course Summary
Objectives:
- Recognize the primary concepts, tools, technologies, and products learned in the course.