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
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 generative AI services and Vertex AI's role.
- Key concepts such as models, prompts, context, and application workflows.
Working with Vertex AI Models
- Navigating the Google Cloud environment for generative AI initiatives.
- 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
- Crafting clear prompts with instructions, context, and examples.
- Enhancing outputs for accuracy, format, tone, and consistency.
- Addressing common prompt issues like 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.
- Integrating prompts, user input, and model responses into a simple workflow.
- Testing application behaviour in a hands-on lab.
- Reviewing practical implementation considerations for real-world projects.
Grounding, Evaluation, and Responsible Use
- The importance of grounding and enterprise context in improving response quality.
- Introductory concepts of retrieval-augmented generation 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 refining prompts over time.
- Identifying realistic next steps for adoption within a team or organisation.
- Course wrap-up and recommendations for further learning.
Requirements
- Fundamental knowledge of cloud computing concepts and standard business application workflows.
- Some prior 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 engaged in 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)
