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Course Outline
Generative AI Basics on Google Cloud
- Defining generative AI and its role in business applications.
- Exploring common use cases such as text generation, chatbots, summarization, and search support.
- An overview of Google Cloud’s generative AI services and the function of Vertex AI.
- Understanding core concepts including models, prompts, context, and application workflows.
Interacting 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 simple experiments and analyzing model responses.
Prompt Engineering and Output Quality
- Crafting clear prompts that include instructions, context, and examples.
- Enhancing output accuracy, formatting, tone, and consistency.
- Addressing common prompt challenges like vague responses and hallucinations.
- Refining prompts iteratively for specific business tasks.
Developing a Basic Generative AI Application
- Designing a fundamental application flow for chat, summarization, or content generation.
- Integrating prompts, user input, and model outputs into a streamlined workflow.
- Testing application performance in a hands-on lab setting.
- Assessing practical implementation factors for real-world projects.
Grounding, Assessment, and Responsible Usage
- Understanding why grounding and enterprise context enhance response accuracy.
- Introduction to retrieval-augmented generation concepts for knowledge-driven applications.
- Basic methodologies for evaluating prompts and outputs.
- Considering security, data privacy, access controls, and responsible AI standards on Google Cloud.
From Prototype to Production Readiness
- Transitioning from proof of concept to a robust business solution.
- Monitoring usage, analyzing results, and continuously refining prompts.
- Identifying actionable next steps for adoption within teams or organizations.
- Course conclusion and suggestions for continued learning.
Requirements
- A fundamental grasp of cloud computing principles and standard business application workflows.
- Familiarity with using the Google Cloud Console or comparable cloud platforms.
- Basic proficiency in programming or scripting.
Target Audience
- Developers and technical specialists creating AI-integrated applications.
- Cloud engineers and solution architects involved in Google Cloud projects.
- Product teams and technical leaders investigating practical generative AI use cases.
7 Hours
Testimonials (2)
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
