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Course Outline

Generative AI Fundamentals on Google Cloud

  • Understanding what generative AI is and its place within business applications.
  • Common use cases for text generation, chat, summarization, and search assistance.
  • Overview of Google Cloud 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 for 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.
  • Handling 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 a chat, summarization, or content generation use case.
  • Connecting prompts, user input, and model responses into a simple workflow.
  • Testing application behavior in a hands-on lab.
  • Reviewing practical implementation considerations for real projects.

Grounding, Evaluation, and Responsible Use

  • Why grounding and enterprise context improve response quality.
  • Introductory 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

  • Moving from a proof of concept to a more reliable business solution.
  • Monitoring usage, reviewing results, and 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 understanding 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.

Target Audience

  • Developers and technical professionals tasked with building AI-enabled applications.
  • Cloud engineers and solution architects working on Google Cloud projects.
  • Product teams and technical managers exploring practical use cases for generative AI.
 7 Hours

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