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Course Outline
Fundamentals of Generative AI on Google Cloud
- Understanding what generative AI is and its role in business applications.
- Common use cases including text generation, chat, summarization, and search assistance.
- An overview of Google Cloud's generative AI services and the role of Vertex AI.
- Key concepts such as models, prompts, context, and application workflows.
Working with Vertex AI Models
- Navigating the Google Cloud environment for generative AI projects.
- Accessing and testing foundation models within Vertex AI.
- Comparing model capabilities for various business scenarios.
- Conducting simple experiments and reviewing model responses.
Prompting and Output Quality
- Writing clear prompts that include instructions, context, and examples.
- Improving output for accuracy, format, tone, and consistency.
- Addressing common prompt issues such as vague responses and hallucinations.
- Practicing iterative prompt refinement for business tasks.
Building a Simple Generative AI Application
- Designing a basic application flow for chat, summarization, or content generation use cases.
- Connecting prompts, user input, and model responses into a streamlined workflow.
- Testing application behavior through hands-on lab exercises.
- Reviewing practical implementation considerations for real-world projects.
Grounding, Evaluation, and Responsible Use
- Understanding why grounding and enterprise context enhance response quality.
- Introduction to retrieval-augmented generation concepts for knowledge-based applications.
- Basic evaluation methods for prompts and outputs.
- Security, data privacy, access control, and responsible AI considerations on Google Cloud.
From Prototype to Next Steps
- Transitioning from a proof of concept to a more robust business solution.
- Monitoring usage, reviewing results, and continuously improving prompts over time.
- Identifying realistic next steps for adoption within a team or organization.
- Course wrap-up and recommendations for further learning.
Requirements
- Fundamental knowledge of cloud computing concepts and typical business application workflows.
- Some experience using the Google Cloud Console or a comparable cloud platform.
- Basic proficiency in programming or scripting.
Audience
- Developers and technical professionals creating AI-enabled applications.
- Cloud engineers and solution architects working on Google Cloud projects.
- Product teams and technical managers investigating practical generative AI use cases.
7 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
