In this course, you’ll learn the ins and outs of Streamlit. You’ll begin by grasping the fundamentals of the Streamlit framework, followed by designing user interfaces with widgets like sliders, buttons, and text input. The course then moves into managing state within a Streamlit app and culminates with the integration of an LLM API for dynamic chatbot responses. The hands-on exercises and real-world scenarios provide an immersive learning experience, ensuring you gain practical skills and knowledge.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. Engage in realistic business scenarios, from a customer service app for a coffee startup to an AI chatbot for a tech firm, building your portfolio and prepping for your next career move all while learning a new skill.
- Grasp the essentials of Streamlit for interactive web app development
- Create user-friendly interfaces with Streamlit's array of widgets
- Manage application state for dynamic user experiences
- Integrate AI LLM models for responsive chatbots
- Leverage Streamlit's latest chat widgets for effective communication
Designing Dynamic Python Applications with Streamlit [4 lessons]
- Understand how Streamlit works, including its strengths, limitations, and its primary uses
- Set up your Streamlit development environment
- Implement basic Streamlit elements like buttons, text, headings, sliders, dropdown boxes, and titles
- Deploy a Streamlit application locally
- Debug and troubleshoot common issues with basic Streamlit elements
- Arrange content effectively using Streamlit's layout features like sidebars, columns, tabs, and expanders
- Determine the best use cases for different layout elements
- Organize Streamlit code with clean, encapsulated functions
- Understand the concept of state in a Streamlit application
- Implement session state to manage user inputs and responses
- Add interactive chat inputs in your application
- Test the state management of your application
- Integrate the OpenAI API with Streamlit to bring the chatbot to life.
- Enhance user interaction using Streamlit's dynamic widgets.
- Implement best practices for API key security.
- Deploy your chatbot application for public access.
The Dataquest guarantee
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.