Get in Touch

Course Outline

Fundamentals of Generative AI on Google Cloud

  • Definition of generative AI and its role in business applications.
  • Typical use cases including text generation, chat, summarization, and search assistance.
  • Overview of Google Cloud generative AI services and the function 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 initiatives.
  • Accessing and testing foundation models within Vertex AI.
  • Comparing model capabilities across various business scenarios.
  • Conducting basic experiments and reviewing model outputs.

Prompting and Output Quality

  • Crafting clear prompts with instructions, context, and examples.
  • Enhancing outputs for accuracy, formatting, tone, and consistency.
  • Addressing common prompt challenges like vague responses and hallucinations.
  • Practicing iterative prompt refinement for business tasks.

Developing a Simple Generative AI Application

  • Designing a basic workflow for chat, summarization, or content generation use cases.
  • Linking prompts, user input, and model responses into a cohesive workflow.
  • Testing application behavior in a hands-on lab environment.
  • Reviewing practical implementation aspects 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.
  • Security, data privacy, access control, and responsible AI considerations on Google Cloud.

From Prototype to Next Steps

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

Requirements

  • Fundamental knowledge of cloud computing concepts and standard business application workflows.
  • Some familiarity with the Google Cloud Console or comparable cloud platforms.
  • Basic proficiency in programming or scripting.

Audience

  • Developers and technical professionals creating AI-enabled applications.
  • Cloud engineers and solution architects involved in Google Cloud projects.
  • Product teams and technical managers investigating practical generative AI use cases.
 7 Hours

Number of participants


Price per participant

Testimonials (2)

Upcoming Courses

Related Categories