Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Generative AI Fundamentals on Google Cloud
- Defining generative AI and its role in business applications.
- Common use cases for text generation, chatbots, summarization, and search assistance.
- An overview of Google Cloud generative AI services and the function of Vertex AI.
- Core concepts including 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 analyzing 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.
- Practicing iterative prompt refinement for business tasks.
Building a Simple Generative AI Application
- Designing a basic application flow for chat, summarization, or content generation use cases.
- Integrating prompts, user input, and model responses into a simple workflow.
- Testing application behavior 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 in 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 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 knowledge of cloud computing concepts and standard business application workflows.
- Some experience using the Google Cloud Console or an equivalent cloud platform.
- Basic proficiency in programming or scripting.
Audience
- Developers and technical professionals developing AI-enabled applications.
- Cloud engineers and solution architects working on Google Cloud initiatives.
- Product teams and technical managers investigating practical generative AI use cases.
7 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
