Google Cloud Generative AI Learning Path

Module 1: Introduction to Generative AI

• Fundamentals of Generative AI.
• Generative AI use cases and applications.
• Responsible AI principles.
• AI ethics and governance.

Module 2: Large Language Models (LLMs)

• Understanding Large Language Models.
• Transformer architecture fundamentals.
• LLM capabilities and limitations.
• Foundation models overview.

Module 3: Prompt Engineering

• Principles of effective prompt design.
• Zero-shot, one-shot, and few-shot prompting.
• Prompt optimization techniques.
• Best practices for prompt engineering.

Module 4: Google Cloud Generative AI Services

• Introduction to Vertex AI.
• Using foundation models in Google Cloud.
• Generative AI Studio overview.
• Model customization and deployment.

Module 5: Building Generative AI Applications

• Developing AI-powered applications.
• Integrating APIs and AI services.
• Chatbots and conversational AI.
• Real-world use cases and implementation.

Module 6: Responsible AI and Security

• Ethical AI considerations.
• Bias detection and mitigation.
• Security, privacy, and governance.
• Responsible AI implementation strategies.

Training Eligibility

• There are no mandatory prerequisites to enroll in the Google Cloud Generative AI Learning Path.
• Anyone interested in Artificial Intelligence and Google Cloud technologies can join.

Recommended Knowledge

• Basic understanding of cloud computing concepts.
• General IT concepts.
• Programming fundamentals are helpful but not mandatory.
• Artificial Intelligence concepts are optional.
• No prior experience in Generative AI is required.