Rapid Prototyping of GenAI Apps with Streamlit

Build and iterate GenAI apps in hours instead of weeks! 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 GitHub or Streamlit Community Cloud for instant feedback and rapid improvement.

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IN COLLABORATION WITH

  • Plan, build, and iterate GenAI ideas quickly by turning a short Python script into an interactive Streamlit app that runs entirely inside Snowflake.

  • Strengthen your app with practical prompt engineering methods, vector search, and RAG to ground responses in real data.

  • Publish your prototype to GitHub, private Snowflake environments, or Streamlit Community Cloud, collect user feedback, and refine confidently without extra infrastructure.

Why Enroll?

Rapid Prototyping of GenAI Apps with Streamlit tackles a simple but costly problem: ideas lose momentum when they linger in notebooks. 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 learn to turn a few lines of Python into a share-ready Streamlit web app, then iterate in hours instead of weeks using Snowflake’s secure data, vector search, and Cortex LLM endpoints (free 120-day trial included). 

You’ll start with a “hello-world” chatbot, layer on prompt engineering and RAG, and publish the result to GitHub, 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.

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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 LLM endpoints, vector search, and your own data to build and refine apps in a production-ready environment.

Instructor

Chanin Nantasenamat

Chanin Nantasenamat

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. Before joining industry, Chanin spent 15 years at Mahidol University 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 the Avalanche customer-review dataset for sentiment insights, all inside Snowflake’s secure environment with a 120-day free trial of Cortex LLM and vector search services.

Elevate answers with structured prompt engineering and Retrieval-Augmented Generation, grounding every response in real product-review data.

Ship your prototype to GitHub, private Snowflake workspaces, or Streamlit Community Cloud, gather feedback, and iterate fast with the course’s MVP playbook.

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Skills you will gain

  • Rapid 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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Learner reviews from other DeepLearning.AI courses

What I loved about the “AI for Everyone” course was the comprehensive coverage of essential AI topics, guided by the expertise of Andrew Ng. The course provided a clear roadmap for initiating and managing AI projects, from project selection to implementation. It also offered insights into building AI teams and introduced the technical tools necessary for AI success

Selami A.
Software QA Manager

Simple enough to make it easy to understand in spite of being a complex topic, inspiring speaker. Time well spent, and a good fit with “lifelong learning” approach.

Chris C.
DeepLearning.AI Learner

What stood out to me about this course was the clarity and simplicity with which complex AI concepts were explained. The real-life examples and case studies helped me grasp the practical implications of AI in different sectors. The interactive nature of the course made learning engaging and enjoyable.

Adeel B.
DeepLearning.AI Learner

I am an educator and looking to incorporate AI into my career and help my colleagues to do the same. The course did a great job explaining AI concepts to people like myself who are just learning about any of this for the first time.

Krystal L.
DeepLearning.AI Learner

I took this course purely out of curiosity. After becoming aware of ChatGPT and Midjourney and then taking a short course on engineering the prompts to get the desired result, I became more intrigued with the topic of AI. I found this most helpful with regards to getting an idea about what AI actually is as opposed to what Hollywood conditioned me to believe it might be.

John S.
DeepLearning.AI Learner

Loved the content. It brought simplicity to the complex topic of AI, separated signal from noise, presented a great flow and covered the most relevant topics.

Andrew’s knowledge and passion about the subject of AI was amazing. It was inspiring to listen to him, even via recorded videos. Its really great to be in this era of technology, as it makes it possible to get access to the wealth of knowledge so easily.

Muhammad S.
DeepLearning.AI Learner

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