Fast Prototyping of GenAI Apps with Streamlit

Overview

Fast Prototyping of GenAI Apps with Streamlit tackles a costly problem: ideas lose momentum when they linger in discussions, drawn-out specifications, and intangibles that slow down the decision-making process. In a field where new GenAI capabilities surface every week, the teams that can show working demos first are the ones that influence roadmaps and win resources. This course gives you that speed advantage. You’ll explore how GenAI streamlines the prototyping workflow, facilitates rapid iteration and validation of product-market fit, and allows anyone, regardless of coding experience, to participate in the app creation process. You’ll learn to turn a few lines of Python into a shareable Streamlit web app, cut down iteration time from weeks to hours using Snowflake’s secure data and coding copilot, and improve the performance of your application easily using Snowflake’s Cortex AI, a fully managed suite of LLMs, RAG, and text-to-SQL services (free 120-day trial included). You’ll start with a basic chatbot, layer on prompt engineering and RAG, and publish the result to Snowflake, or Streamlit Community Cloud for real-time feedback. By course end, you’ll leave with a working GenAI app, a repeatable MVP-first framework, and the skills to validate any new idea as soon as it strikes.

Syllabus

Introduction to Prototyping Generative AI Applications

Learn how to rapidly transform ideas into working GenAI prototypes using Streamlit and Snowflake. You'll build your first Gen AI-powered app with real data, master the MVP mindset for fast development, and discover how generative AI accelerates coding, debugging, and prototyping workflows.

Fast Prototyping with Streamlit in Snowflake

Transform your basic prototype into a deployable, shareable MVP by integrating Snowflake Cortex for AI-powered insights, building interactive user interfaces, and mastering deployment to make your app accessible to real users. You'll parse unstructured data, create streamlined workflows, and learn multiple deployment options including Streamlit Community Cloud and Snowflake Native Apps.

Iterative Improvement

Build intelligent data insights using Snowflake Cortex functions to automatically summarize, analyze sentiment, and extract patterns from customer reviews. You'll seamlessly combine structured and unstructured data, implement RAG (Retrieval-Augmented Generation) to enhance AI responses with real customer data, and use data augmentation techniques to improve answer quality—all without writing complex analytical logic, while preparing your app for real-world user testing.