Generative AI with Vertex AI: Prompt Design | GSP1151 Qwiklabs Walkthrough (Full Lab Solution)
This video is a complete, step-by-step walkthrough for the Google Cloud Skills Boost lab, "Generative AI with Vertex AI: Prompt Design" (GSP1151).
This hands-on lab introduces you to the essential techniques of prompt engineering using Gemini models on Vertex AI Workbench. Mastering these skills is key to getting high-quality, reliable, and predictable results from large language models (LLMs).
What you will learn in this lab:
Prompt Engineering Best Practices: Discover how to be concise, specific, and well-defined in your prompts.
Handling Hallucinations: Learn strategies to reduce irrelevant responses and "guardrail" your model.
Reducing Output Variability: See how converting generative tasks to classification tasks can improve consistency.
Improving Response Quality with Examples: Understand the difference between zero-shot, one-shot, and few-shot prompting techniques and how to use them effectively.
Working with Vertex AI: Setup a Vertex AI Workbench notebook instance and run a Python notebook to interact with the Gemini API.
🕒 Timestamps:
0:00 - Introduction and Lab Overview
0:36 - Starting the Lab and Google Cloud Console Setup
1:50 - Task 1: Open the Notebook in Vertex AI Workbench
2:53 - Task 2: Setup the Notebook (Installing Libraries and Setting up Client)
4:59 - Task 3: Prompt Engineering Best Practices (Be Concise, Specific, Ask One Task)
5:19 - Run through Hallucination Reduction Techniques
5:30 - Run through Reducing Output Variability (Generative vs. Classification)
5:59 - Final Code Execution and Check My Progress
6:57 - Task 5: Improve Response Quality by Including Examples
7:35 - Conclusion and Final Assessment
👍 If this video helped you complete the lab, please hit the like button and subscribe for more Google Cloud, Vertex AI, and Qwiklabs walkthroughs!
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