Fast Prototyping of GenAI Apps with Streamlit
Build and iterate GenAI apps in hours instead of days! Start with a simple chatbot, then add prompt engineering and RAG powered by Snowflake’s secure data and LLM services, then push your prototype to Snowflake or Streamlit Community Cloud for instant feedback and quick improvement.
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IN COLLABORATION WITH
Plan, build, launch fast: Apply a rapid-prototyping framework to scope, build, and deploy an interactive GenAI app.
Build inside Snowflake: Develop in Snowflake’s secure data environment, tap its LLM-powered insights, and publish to Snowflake or Streamlit Community Cloud for instant feedback.
Iterate toward production: Use a prioritized feedback loop plus prompt engineering and RAG to refine your prototype and move it confidently toward real-world deployment.
Why Enroll?
Fast Prototyping of GenAI Apps with Streamlit tackles a simple but costly problem: product ideas lose momentum when they linger in discussions, drawn-out specifications, and intangibles that slow down the decision-making process. In the constantly evolving world of generative AI, the ability to prototype quickly is a significant competitive advantage. Teams that can show working demos and iterate fast influence roadmaps, shape decisions, and win resources. Generative AI makes this speed accessible to everyone.
This course gives you that speed advantage. You’ll explore how GenAI streamlines the prototyping workflow, facilitates fast 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, and improve the performance of your application easily using Cortex AI (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.
What is Streamlit?
Streamlit is an open-source Python library that turns a few lines of code into interactive, data-driven web apps in minutes, no front-end skills required. Its simplicity and speed have made it a go-to tool for thousands of developers who need to share insights or prototype AI features fast.
In partnership with
We partnered with Snowflake so you can turn ideas into GenAI prototypes fast and spend more time acting on feedback. Inside Snowflake’s secure platform, you’ll pair Streamlit with Cortex AI to build and refine apps in a secure and production-ready environment.
Instructor
Chanin Nantasenamat
Dr. Chanin Nantasenamat is a Senior Developer Advocate at Snowflake, where he creates educational content for Streamlit and teaches developers to build interactive data apps. Known online as “The Data Professor,” he shares free tutorials on data science, AI, and bioinformatics with a global YouTube audience of over 200,000 subscribers. Before joining the industry, Chanin spent 15 years at Mahidol University in Thailand as a professor of bioinformatics, published nearly 170 papers, and led the university’s Center of Data Mining and Biomedical Informatics.
- 1 Course, 3 modules
- Self-paced
- Intermediate
Course Syllabus
Build GenAI prototypes in hours, not weeks
Build share-ready Generative AI apps without wrestling with front-end code. In this course, you’ll start from a few lines of Python and Streamlit, the open-source library that turns scripts into interactive web apps, then incrementally shape your prototype into a more capable LLM application.
Build an interactive Streamlit analytics assistant that mines a customer-review dataset for sentiment insights within your own Snowflake account (120-day free trial included).
Improve response quality with structured prompt engineering and RAG, grounding each answer in the review data.
Ship your prototype to internal Snowflake workspaces, or publish it to Streamlit Community Cloud, gather feedback, and iterate fast with the course’s MVP playbook.
Skills you will gain
- Rapid MVP Prototyping
- Fast MVP Prototyping
- Generative AI App Development
- Prompt Engineering
- Retrieval Augmented Generation (RAG)
- Vector Search
- Iterative Development & Feedback Loops
- Cloud Deployment
Who this course is for
If you’re comfortable coding in Python and familiar with generative AI and the basics of prompting, this course is perfect for you! Basic knowledge of SQL is helpful but optional.
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