
Developing LLM App Frontends with Streamlit
Автор:
Категорії:
Останнє оновлення:
November 2024
Субтитри:
English, Français, Deutsch, Español, العربية, Nederlands, Vlaams, हिन्दी, हिंदी, Bahasa indonesia, 日本語 (にほんご/にっぽんご), Português, Română
Аудіо:
English
Огляд
Why Choose Streamlit for Your Learning Journey?
The rise of Large Language Models (LLMs) marks a new era in technology, and you’ve likely come across discussions about leveraging LLMs for innovative AI applications.
For an AI application to be user-friendly, it’s essential to have a frontend that seamlessly interacts with your LLM and enhances the overall user experience.
That’s where Streamlit shines!
Streamlit is a fantastic open-source Python library that allows you to quickly create and share machine learning and data science applications with a global audience.
Our project begins with a beginner-friendly section that covers everything you need to know about Streamlit. Following that, we’ll dive into building the user interface for your LLM-based Q&A application.
What’s All This About Projects?
We often hear from students, "I’m eager to work on more projects!".
We appreciate that enthusiasm because undertaking projects is the most effective way to learn. Unique and challenging projects can significantly enhance your portfolio, grabbing the attention of potential employers.
Plus, there’s a satisfying joy in creating something tangible!
That’s why we’ve launched ZTM Projects, a collection of extensive practice and portfolio projects designed to help you expand your knowledge, acquire new skills, and sometimes simply enjoy the process!
What More Should You Know?
By joining ZTM, you’ll unlock access to all our courses, bytes, and projects.
You’ll also gain entry to our exclusive live online community classroom, where you can connect with thousands of students, alumni, mentors, teaching assistants, and instructors.
Most importantly, you’ll be learning from industry expert Andrei, who brings real-world experience with Streamlit and LLMs. He shares the precise knowledge he applies in his professional role.
Additionally, all ZTM courses are regularly updated to keep pace with industry changes, establishing this course as your reliable resource for mastering Streamlit now and in the future.
Join thousands of Zero To Mastery graduates who have secured positions at top companies like Google, Tesla, Amazon, Apple, IBM, JP Morgan, and Facebook.
Our graduates come from diverse backgrounds, ages, and experiences, with many starting as complete beginners.
You can join their ranks!
There’s no risk involved. Begin your learning adventure today, and if this course doesn’t meet your expectations, we offer a full refund within 30 days—no questions asked.
Структура
Структура:
Всього розділів: 4
Всього уроків: 26
1. Introduction
5 уроків
2. Streamlit Fundamentals
12 уроків
3. Building a Frontend for the LLM-powered Q&A App using Streamlit
8 уроків
4. Where To Go From Here?
1 урок
Автор
Ціна
Unlimited access to all courses, projects + workshops, and career paths
Access to our private Discord with 400,000+ members
Access to our private LinkedIn networking group
Custom ZTM course completion certificates
Live career advice sessions with mentors, every month
Full access to all future courses, content, and features
Access to our private Discord with 450,000+ members
Unlimited access to all courses, projects, and career paths
Unlimited access to all bootcamps, bytes, and projects, and career paths
Access to our private LinkedIn networking group with 100,000+ members
Unlimited access to all courses, projects + workshops, and career paths
Access to our private Discord with 400,000+ members
Access to our private LinkedIn networking group
Custom ZTM course completion certificates
Live career advice sessions with mentors, every month
Full access to all future courses, content, and features
Access to our private Discord with 450,000+ members
Unlimited access to all courses, projects, and career paths
Unlimited access to all bootcamps, bytes, and projects, and career paths
Access to our private LinkedIn networking group with 100,000+ members
Unlimited access to all courses, projects + workshops, and career paths
Access to our private Discord with 400,000+ members
Access to our private LinkedIn networking group
Custom ZTM course completion certificates
Live career advice sessions with mentors, every month
Full access to all future courses, content, and features
Access to our private Discord with 450,000+ members
Unlimited access to all courses, projects, and career paths
Unlimited access to all bootcamps, bytes, and projects, and career paths
Access to our private LinkedIn networking group with 100,000+ members
Часто задавані питання
Are there any prerequisites for this course?
Are there any prerequisites for this course?
- You should have a basic understanding of Python. If you’re new to Python, we recommend starting with our Python Bootcamp course first!
- To successfully complete this project, you’ll need to have previously developed an LLM-powered Q&A application, as you’ll be working on the frontend for that app. If you haven’t built it yet, feel free to join our Build an LLM-powered Q&A App using LangChain, OpenAI and Python project, which should take about 3 hours!
Do you provide a certificate of completion?
Do you provide a certificate of completion?
Absolutely! We offer a beautifully designed certificate, and you can also showcase Zero To Mastery Academy in the education section of your LinkedIn profile.
Are there subtitles?
Are there subtitles?
Yes, indeed! We provide high-quality subtitles in 11 languages, including English, Spanish, French, German, Dutch, Romanian, Arabic, Hindi, Portuguese, Indonesian, and Japanese.
You can customize the subtitle appearance by adjusting the text size, color, background, and more to suit your preferences!
Still have more questions about the Academy?
Still have more questions about the Academy?
If you have additional inquiries about the Academy membership, don’t worry! You can find further answers here.
Гарантія
Термін гарантії 30 днів, з моменту покупки.

Developing LLM App Frontends with Streamlit