CF

Developing LLM App Frontends with Streamlit

1h 43m 52s
English
Paid

This byte-sized course will teach Streamlit fundamentals and how to use Streamlit to create a frontend for your LLM-powered applications.

In this project-based course you'll learn to use Streamlit to create a frontend for an LLM-powered Q&A application. Streamlit is an open-source Python library that simplifies the creation and sharing of custom frontends for machine learning and data science apps with the world.

About the Author: Zero To Mastery

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Zero To Mastery (ZTM) is a Toronto-based online coding academy founded by Andrei Neagoie, originally a senior developer at large Canadian tech firms before turning to teaching full-time. The academy's signature is the cohort-based bootcamp track combined with a deep self-paced course library, all aimed at career-changers and self-taught developers preparing to land software-engineering roles at top companies.

The instructor roster has grown well beyond Andrei to include other senior practitioners: Daniel Bourke (machine learning), Aleksa Tešić (DevOps), Jacinto Wong, and others. Courses cover the full software-engineering career path: web development with React and Next.js, Python, machine learning and deep learning, DevOps and cloud, system design, mobile, and the algorithm / data-structure interview prep that gates engineering jobs.

The CourseFlix listing under this source carries over 120 ZTM courses spanning that full range. Material is paid; ZTM itself runs on a monthly / annual membership model. The teaching style favours long-form, project-based courses where students build complete portfolio-quality applications rather than disconnected feature tutorials.

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#1: Introduction
All Course Lessons (20)
#Lesson TitleDurationAccess
1
Introduction Demo
03:08
2
Introduction to Streamlit
04:15
3
Streamlit Main Concepts
05:28
4
Displaying Data on the Screen: st.write() and Magic
05:32
5
Widgets Part 1: text_input, number_input, button
05:10
6
Widgets Part 2: checkbox, radio, select
07:25
7
Widgets Part 3: slider, file_uploader, camera_input, image
08:15
8
Layout: Sidebar
01:57
9
Layout: Columns
04:30
10
Layout: Expander
02:10
11
Displaying a Progress Bar
03:08
12
Session State
07:35
13
Callbacks
06:08
14
Project Introduction and Library Installation
04:09
15
Defining Functions
06:14
16
Creating the Sidebar
06:04
17
Reading, Chunking, and Embedding Data
06:22
18
Asking Questions and Getting Answers
05:25
19
Saving the Chat History
06:00
20
Clearing Session State History using Callback Functions
04:57
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Frequently asked questions

What is Developing LLM App Frontends with Streamlit about?
This byte-sized course will teach Streamlit fundamentals and how to use Streamlit to create a frontend for your LLM-powered applications.
Who teaches this course?
It is taught by Zero To Mastery. You can find more courses by this instructor on the corresponding source page.
How long is the course?
It contains 20 lessons with a total runtime of 1 hour 43 minutes. Every lesson is available to watch online at your own pace.
Is it free to watch?
It is part of CourseFlix's premium catalog. A subscription unlocks the full video player; the course description, table of contents, and preview information are available to everyone.
Where can I watch it online?
The course is available to watch online on CourseFlix at https://courseflix.net/course/developing-llm-app-frontends-with-streamlit. The page hosts every lesson with the integrated video player; no download is required.