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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, summarisation, and search assistance.
  • 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 with instructions, context, and examples.
  • Enhancing 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.
  • 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 for 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 understanding of cloud computing concepts and standard business application workflows.
  • Some experience using the Google Cloud Console or a comparable cloud platform.
  • Basic programming or scripting proficiency.

Target Audience

  • Developers and technical professionals constructing AI-enabled applications.
  • Cloud engineers and solution architects working on Google Cloud initiatives.
  • Product teams and technical managers exploring practical generative AI use cases.
 7 Hours

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