Udemy

Learn Streamlit Python

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  • 6,001 名學生
  • 更新於 10/2025
  • 可獲發證書
4.6
(694 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
3 小時 58 分鐘
教學語言
英語
授課導師
Jesse E. Agbe
證書
  • 可獲發
  • *證書的發放與分配,依課程提供者的政策及安排而定。
評分
4.6
(694 個評分)
14次瀏覽

課程簡介

Learn Streamlit Python

Create Beautiful Data Apps and Machine Learning Web Apps In Python Faster with Streamlit


Are you having difficulties trying to build web applications for your data science projects? Do you spend more time trying to create a simple MVP app with your data to show your clients and others? Then let me introduce you to Streamlit - a python framework for building web apps.


Welcome to the coolest  online resource for learning how to create Data Science Apps and Machine Learning Web Apps using the

awesome Streamlit Framework and Python.

This course will teach you Streamlit - the python framework that saves you from spending days and weeks in creating

data science and machine learning web applications.


In this course we will cover everything you need to know concerning streamlit such as

  • Fundamentals and the Basics of Streamlit ;

- Working with Text

- Working with Widgets (Buttons,Sliders,

- Displaying Data

- Displaying Charts and Plots

 - Working with Media Files (Audio,Images,Video)

- Streamlit Layouts

- File Uploads

- Streamlit Static Components

  • Creating cool data visualization apps

  • How to Build A Full Web Application with Streamlit


By the end of this exciting course you will be able to

  • Build data science apps in hours not days

  • Productionized your machine learning models into web apps using streamlit

  • Build some cools and fun data apps

  • Deploy your streamlit apps using Docker,Heroku,Streamlit Share and more


Join us as we explore the world of building Data and ML Apps.

See you in the Course,Stay blessed.


Tips for getting through the course

  • Please write or code along with us do not just watch,this will enhance your understanding.

  • You can regulate the speed and audio of the video as you wish,preferably at -0.75x if the speed is too fast for you.

  • Suggested Prerequisites is understanding of Python

  • This course is about Streamlit an ML Framework to create data apps in hours not weeks. We  will try our best to cover some concepts for the beginner and the pro .


課程章節

  • 14 個章節
  • 125 堂課
  • 第 1 章 Introduction
  • 第 2 章 Module 02 - Data Visualization In Streamlit
  • 第 3 章 Module 02 - Streamlit Components & Themes
  • 第 4 章 Module 03 - Project Section - Building Streamlit Apps - NLP Apps
  • 第 5 章 Module 03 - Project Section - Building Streamlit Apps - Text Analysis Apps
  • 第 6 章 Project - Building Streamlit Apps -Data Apps
  • 第 7 章 Module 03 - Project Section - Building Streamlit Apps - Machine Learning Apps
  • 第 8 章 Project - Building Streamlit Apps - CRUD Apps (Create Read Update Delete)
  • 第 9 章 Project - Building a CRUD(Create Read Update Delete) App In Streamlit
  • 第 10 章 Project - Build Streamlit Apps - End to End (StreamBible)
  • 第 11 章 Module 04 - Deploying Streamlit Apps
  • 第 12 章 Module 05 - Streamlit Session States
  • 第 13 章 Streamlit Projects - Misc Apps
  • 第 14 章 Streamlit For LLM Apps

課程內容

  • Learn the basics of Streamlit Framework
  • Use Streamlit to create Machine Learning Web Apps and Data Apps
  • Deploying Streamlit Python Web Applications


評價

  • U
    Udemy User
    3.0

    The content is fine -- esp. it you can get it on sale. It's a useful way to read st documentation in a guided way. The instructor's accent is fine -- English is not my first language either and I sympathize. BUT the teacher needs to learn to ENUNCIATE. The accent is not an issue; the mumbling is. To improve please take a short public speaking course and learn to pronounce each word. Otherwise, a slightly outdated course that's mostly useful. I don't regret buying it.

  • P
    Paulo
    5.0

    Awesome - learnt and developed a number of Apps.

  • D
    Dody
    5.0

    so far so good

  • M
    Markus Schneider
    5.0

    As far as I am concerned, the course is excellent! Great videos with sufficient details that build up to substance. Jesse's narrative is perfectly fine.

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