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Course Outline

Fundamentals of Generative AI on Google Cloud

  • Definition of generative AI and its role in business applications.
  • Common use cases including text generation, chat, summarization, and search assistance.
  • Overview of Google Cloud's generative AI services and the pivotal role of Vertex AI.
  • Core 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 Strategies and Output Quality

  • Crafting clear prompts that include 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 specific business tasks.

Developing a Simple Generative AI Application

  • Designing a basic application flow for use cases such as chat, summarization, or content generation.
  • Integrating prompts, user input, and model responses into a coherent workflow.
  • Testing application behavior in a hands-on lab setting.
  • Reviewing practical implementation considerations for real-world projects.

Grounding, Evaluation, and Responsible Use

  • Understanding how grounding and enterprise context improve response quality.
  • Introduction to retrieval-augmented generation concepts for knowledge-based applications.
  • Basic methods for evaluating prompts and outputs.
  • Key considerations for security, data privacy, access control, and responsible AI on Google Cloud.

From Prototype to Next Steps

  • Transitioning from proof of concept to a robust business solution.
  • Monitoring usage, reviewing results, and continuously improving prompts.
  • Identifying realistic next steps for adoption within a team or organization.
  • Course wrap-up and recommendations for further learning.

Requirements

  • Foundational understanding of cloud computing principles and typical 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 creating 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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