• views: 161
• date: 13 June 2023
• posted by: voska89

Learn end-to-end features of Streamlit to build Data apps for Analytics- Data Engineering, Data Science
What you'll learn
Learn the basic and some advanced features of Streamlit
Hands-on streamlit features to build UI widgets
How to build Data apps/Web apps for Data Science and Data Analytics applications
How to deploy Streamlit data app from GitHub to community cloud for Free
Overview of Data Apps for analytics
Requirements
Basic understanding of python programming
Description
Welcome to "Building Data Apps with Streamlit"! In this comprehensive course, you will learn how to leverage the power of Streamlit to build interactive and user-friendly data applications.Streamlit is a Python library that allows you to quickly and easily create web-based data apps with just a few lines of code. It simplifies the process of building interactive dashboards, visualizations, and data exploration tools, making it an ideal choice for data scientists, analysts, and developers.Here's a breakdown of the main topics covered in the course:1. Introduction Welcome to the courseWhat is Streamlit and Why Learn Streamlit Getting started and Installation 2. Displaying text/messages in Streamlit Different ways to display text on the app- markdown, title, header, sub-header, help text, LaTex3. Displaying Data on the App Different ways to display data, tabular data in streamlitHow to display/format dataframe using streamlitHow to display Metrics/KPIs and static table in Stream4. Input Widgets Widgets in Streamlit Button, Download-button and Checkbox Radio Buttonselect boxMulti values selection, Sliding barText input( widget to input single text line)Widgets to input number, Date and TimeText Area to input larger text, File upload 5. Visualizations and Chart in Streamlit Introduction Line chart, Bar chart, Area chart and PyplotAltair chart, Plotly, Bokeh Interactive ChartPydeck and Map using streamlit6. Layout and Containers in StreamlitIntroductionSidebarColumnsMulti Tabs layoutExpanderContainerEmpty7. Status ElementIntroduction to status widgetsWidgets for status messages-warning, error, success, exceptions, waiting8. Control Flow in StreamlitIntroduction How to halt the processing of the App using Control flowForm and Form Submit button9 Advanced Concepts9.1 Caching in StreamlitIntroduction to Caching in streamlitHow to improve the app's performance using Caching 9.2 Session StateIntroductionHow to use session state to populate widget9.3 Theming and Page ConfigurationIntroduction How to configure Theme and Page in  Streamlit App10. Deploy and share streamlit App using CloudIntroduction to streamlit community cloudIntegrate GitHub to community cloud and deploy app11. Project: Build and Deploy Work Order Management AppIntroduction to Work Order Management AppHigh level design and Pseudocode Development and Deployment of the App12. Congratulations and Bonus chapter
Who this course is for
Data scientists, Data professionals and anyone who is interested in creating UI apps for analytics
Homepage

https://www.udemy.com/course/streamlit-new-comprehensive-course-for-building-data-apps/

   
   
   

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