What Python experience do I need for this Streamlit course?

You should have intermediate Python skills, including familiarity with functions, libraries, and basic data structures. Experience with pandas and machine learning concepts is helpful but not required.

How is Streamlit different from other Python web frameworks?

Streamlit is designed specifically for data apps and AI applications. Unlike Flask or Django, you don't need to write HTML, CSS, or JavaScript—everything is pure Python, making it faster to build interactive dashboards and deploy machine learning models.

Can I use Streamlit for production AI applications?

Streamlit supports enterprise features like authentication, caching, and database connections. Many companies use Streamlit dashboards in production environments, and Streamlit Cloud makes deployment straightforward for both prototypes and production apps.

What types of AI models work with Streamlit?

Streamlit works with any Python-based machine learning framework including scikit-learn, TensorFlow, PyTorch, and Hugging Face models. You'll learn to integrate pre-trained models for text classification, image recognition, and tabular data predictions.

Will I learn to deploy my Streamlit applications?

Absolutely. The course covers deployment strategies using Streamlit Cloud, which integrates directly with GitHub for seamless deployment. You'll learn to share your AI applications publicly or privately with just a few clicks.

Does this course cover Snowflake Streamlit integration?

While the course focuses on core Streamlit functionality and deployment to Streamlit Cloud, you'll learn database connection patterns that apply to various platforms including Snowflake Streamlit apps.

Course

Build AI Applications with Streamlit

Learn Streamlit to build and deploy interactive AI applications with Python in this hands-on course.

This course includes

Skill level
Intermediate
Time to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary
1 hour
Projects
1
Prerequisites
1 course
We suggest you complete the following courses before you get started with Build AI Applications with Streamlit:
Learn Intermediate Python 3

About this course

In this Streamlit course, you’ll learn to create interactive dashboards and deploy machine learning models through intuitive Python interfaces. You’ll master essential Streamlit components including widgets, layouts, and session state management, then integrate real AI models from Hugging Face to build production-ready applications. By the end of this Streamlit course, you’ll understand how to visualize data, manage application state, connect to databases, and deploy your apps to Streamlit Cloud. Whether you’re building prototypes or production tools, you’ll gain the practical skills to transform Python scripts into engaging web applications that showcase your AI models.

Skills you'll gain

Build interactive AI dashboards
Deploy models to Streamlit Cloud
Integrate machine learning predictions
Manage session state in Streamlit

Syllabus

Build AI Applications with Streamlit
Learn Streamlit to build interactive AI applications from scratch with Python.

lesson Build AI Applications with Streamlit
article Deploying AI applications to Streamlit Community Cloud
project Build an AI Image Classification Dashboard with Streamlit
quiz Build AI Applications with Streamlit Quiz
informational Build AI Applications with Streamlit Next Steps
Certificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.

The platform

Hands-on learning

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Explore features

Projects in this course

practice Project
Build an AI Image Classification Dashboard with Streamlit
Build a professional web application for image classification using Streamlit and Hugging Face transformers, featuring real-time predictions, classification history, and analytics visualization.

Earn a certificate of completion

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Reviews from learners

The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.
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Codecademy Learner @ USA
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Codecademy Learner @ UK
Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.
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Codecademy Learner @ USA

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Frequently asked questions about Build AI Applications with Streamlit

You should have intermediate Python skills, including familiarity with functions, libraries, and basic data structures. Experience with pandas and machine learning concepts is helpful but not required.

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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.
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Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
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Build AI Applications with Streamlit

About this course

Skills you'll gain

Syllabus