This webinar was a great introduction to the AI Skills Quest, a program designed to help developers like me learn about generative AI and Vertex AI. It gave me a solid understanding of the fundamentals of prompt engineering, responsible AI, and how to integrate these concepts into my projects.
The demo on energy assessment was particularly insightful. It showed how to start with simple prompts, gradually add system instructions, and ultimately transition to a Python code implementation.
The webinar also delved into the intermediate learning path, focusing on more complex use cases like urban planning. The demo using Streamlit was eye-opening, showcasing how quickly I can turn my Python code into a web app.
The speaker emphasized the importance of iterating, using quality data sources, and evaluating my AI solutions effectively.
I have completed the begginer learning path and am really excited to continue working on the AI Skills Quest courses. They provide a wealth of resources and sample code, which I can use to build my own AI projects. Iām especially intrigued by the prospect of using Gemini and Vertex AI to create innovative applications that solve real-world problems.
š§ Beginner Learning Path
The beginner learning path focuses on the core concepts of generative AI, prompt engineering, and responsible AI. It uses a real-world example of home energy efficiency assessment to illustrate how these concepts can be applied in practice.
š Intermediate Learning Path
This learning path delves into more complex scenarios, like urban planning, which require multimodal inputs, system integrations, and user-friendly interfaces. The webinar showed how to build a basic web application using Streamlit to plan green spaces, demonstrating the power of combining generative AI with frontend development.