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
Generative AI Fundamentals on Google Cloud
- What generative AI is and how it fits into business applications
- Common use cases including text generation, chatbots, summarisation, 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 in Vertex AI
- Comparing model capabilities across different business scenarios
- Running simple experiments and reviewing model responses
Prompting and Output Quality
- Writing clear prompts with instructions, context, and examples
- Improving outputs for accuracy, format, tone, and consistency
- Addressing common prompt issues such as vague responses and hallucinations
- Practising iterative prompt refinement for business tasks
Building a Simple Generative AI Application
- Designing a basic application flow for chat, summarisation, or content generation use cases
- Connecting 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
- How grounding and enterprise context enhance 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 reliable 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
- A basic understanding of cloud computing concepts and common business application workflows
- Some prior experience using the Google Cloud Console or a similar cloud platform
- Basic programming or scripting experience
Audience
- Developers and technical professionals building AI-enabled applications
- Cloud engineers and solution architects working on Google Cloud projects
- Product teams and technical managers exploring 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)
