Complete Guide to Data Science Applications with Streamlit
Learn how to build and deploy data science applications in Python
Updated on Feb, 2025
Language - English
Development ,Data Science,Python
Lectures -142
Resources -24
Duration -9.5 hours
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Course Description
Analyzing data and building machine learning models is one thing. Packaging these analyses and models so that they are shareable is a different ball game altogether.
This course aims to teach you the fastest and easiest way to build and share data applications using Streamlit. You don't need any experience in building front-end applications for this. Here are some of the things you can expect to cover in this course:
Python Crash Course
NumPy Crash Course
Introduction to Streamlit
Integrating Matplotlib and Seaborn in Streamlit
Using Altair and Vega-Lite in Streamlit
Understand all Streamlit Widgets
Upload and Process Files
Build an Image Processing Application
Develop a Natural Language Processing Application
Integrate Maps with Streamlit
Implement Plotly Graphs
Authenticate Your Applications
Laying Out your Application in Streamlit
Developing with Streamlit Components
Deploying Data Applications
At the end of the course, you will have built several applications that you can include in your data science portfolio. You will also have a new skill to add to your resume.
The course also comes with a 30-day money-back guarantee. Enroll now and if you don't like it, you will get your money back, no questions asked.
Goals
- Building Data Applications with Streamlit
- Integrating Matptlotlib & Seaborn in Streamlit
- Plotly Visualizations in Streamlit
- Authenticating Streamlit Applications
- Deploying Streamlit Applications
- Using Streamlit Components
- Altair Visualizations in Streamlit
Prerequisites
- Basic Python Programming, however, a Python crash course is included
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
2 Lectures
-
Introduction
02:25
02:25
-
Introduction to Streamlit
04:00
04:00
Python Crash Course
20 Lectures
Package Management in Python
2 Lectures
NumPy Crash Course
8 Lectures
Pandas Crash Course
16 Lectures
Matplotlib with Streamlit
13 Lectures
Streamlit with Seaborn
10 Lectures
Extras
1 Lectures
File Upload
1 Lectures
Mapping
1 Lectures
Image Processing Application
11 Lectures
Streamlit components
1 Lectures
Streamlit Authentication
1 Lectures
Plotly with Streamlit
12 Lectures
Streamlit with Altair
24 Lectures
Streamlit Layout
1 Lectures
Add Interactivity in Streamlit
7 Lectures
Natural Language Processing
7 Lectures
Deploy Streamlit Application
2 Lectures
Course Code
1 Lectures
Instructor Details
Derrick Mwiti
Derrick Mwiti is a data scientist who has a great passion for sharing knowledge. He is an avid contributor to the data science community.
Experienced in data science, machine learning, and deep learning with a keen eye for building machine learning communities.
Derrick works as a machine learning developer advocate, where he helps companies build products that developers want. It involves getting feedback to the companies as well as getting feedback to developers.
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