About This Course

Who this course is for:

  • Individuals interested in building data science and machine learning applications in Python

What you’ll learn: 

  • Python crash course
  • NumPy crash course
  • Introduction to Streamlit
  • Integrating Matplotlit 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

Requirements: 

  • Basic Python Programming, however a Python crash course is included

Analyzing data and building machine learning models is one thing. Packaging these analyses and models such that they are sharable is a different ball game altogether.

This course aims at teaching 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.

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.

Our Promise to You

By the end of this course, you will have learned how to use Streamlit.

30 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today and learn more about Steamlit.

Course Curriculum

Section 1 - Introduction
Introduction To Streamlit 00:00:00
Download All The Course Files 00:00:00
Section 2 - Python Crash Course
Section Introduction 00:00:00
Install Anaconda 00:00:00
The Data Science Process 00:00:00
Python For Data Science 00:00:00
A Linux Launch Notebook 00:00:00
B Windows Launch Notebook 00:00:00
Folder Structure 00:00:00
Python Operations And Comments 00:00:00
Python Types 00:00:00
Lists And Indexing 00:00:00
Lists – Negative Indexing 00:00:00
Python Dictionaries 00:00:00
Python Tuples 00:00:00
Python Sets 00:00:00
Python Boolean Operators 00:00:00
Conditional Statements 00:00:00
Python Functions 00:00:00
Python For Loop 00:00:00
Python While Loop 00:00:00
Python Map Function 00:00:00
Python Range Function 00:00:00
Python Exercise 00:00:00
Python Solutions 00:00:00
Section 3 - Package Management In Python
Section Introduction 00:00:00
Virtual Environment 00:00:00
Pip Practical 00:00:00
Anaconda Package Installation 00:00:00
Section 4 - Numpy Crash Course
NumPy Introduction 00:00:00
NumPy Zeros, Ones, And Linspace 00:00:00
Checking NumPy Documentation 00:00:00
One Dimensional Indexing 00:00:00
Multi Dimensional Indexing 00:00:00
Broadcasting In NumPy 00:00:00
Operations In NumPy 00:00:00
NumPy Exercise 00:00:00
NumPy Solutions 00:00:00
Section 5 - Pandas Crash Course
Section Introduction 00:00:00
Introduction To Pandas 00:00:00
Pandas Dataframes 00:00:00
Resetting The Index 00:00:00
Dropping Columns 00:00:00
Dealing With Null Values 00:00:00
Creating New Columns 00:00:00
Selecting In Pandas 00:00:00
Grouping Data 00:00:00
Exporting Data Frames 00:00:00
Loading Data 00:00:00
Pivot Tables 00:00:00
Pandas Project 00:00:00
Solutions Part 1 00:00:00
Solutions Part 2 00:00:00
Solutions Part 3 00:00:00
Solutions Part 4 00:00:00
Solutions Part 5 00:00:00
Solutions Part 6 00:00:00
Solutions Part 7 00:00:00
Section 6 - Visualization Guide
Visualization Guide 00:00:00
Section 7 - Matplotlib With Streamlit
Matplotlib Introduction 00:00:00
Set Up Environment 00:00:00
First Visual 00:00:00
Markdown 00:00:00
Bar Plot 00:00:00
Create Horizontal Bar 00:00:00
Create Scatter Plot 00:00:00
Histogram 00:00:00
Pie Chart 00:00:00
Make Sub Plots 00:00:00
Create Four Sub Plots 00:00:00
Figure And Axes 00:00:00
Four Plots With Figure And Axes 00:00:00
Section 8 - Streamlit With Seaborn
Section Introduction 00:00:00
Data Introduction 00:00:00
App Introduction 00:00:00
Create Count Plot 00:00:00
Stripplot And Violin Plot 00:00:00
Exercise 00:00:00
Show Trend 00:00:00
Seaborn Sub Plots Exercise 00:00:00
Figure And Axes 00:00:00
Word Cloud 00:00:00
Section 9 - Extras
Extras – Page Title, Favicon Etc 00:00:00
Section 10 - File Upload
File Upload 00:00:00
Section 11 - Mapping
Map 00:00:00
Section 12 - Image Processing Application
Section Introduction 00:00:00
Show Image 00:00:00
Rotate Image 00:00:00
Create Thumbnail 00:00:00
Cropped Image [Exercise Included] 00:00:00
[Exercise] Merging Images 00:00:00
Flip Image 00:00:00
Convert To Black And White 00:00:00
Sharpen The Image 00:00:00
Enhance The Edges 00:00:00
Contrast The Image 00:00:00
Section 13 - Streamlit Components
Section Introduction 00:00:00
Integrate Streamlit Components 00:00:00
Section 14 - Streamlit Authentication
Authenticate Your App 00:00:00
Section 15 - Plotly With Streamlit
Section Introduction 00:00:00
Plotly Introduction 00:00:00
Load The Data 00:00:00
Create Pie Chart – Categorical Plot 00:00:00
Create Donut Chart 00:00:00
Create Scatter Plot 00:00:00
Scatter With Columns 00:00:00
Show The Trend 00:00:00
Create Bar Chart 00:00:00
Stack The Bar Chart 00:00:00
Create Animations 00:00:00
Make Subplots 00:00:00
Section 16 - Streamlit With Altair
Altair Introduction 00:00:00
Vega Lite 00:00:00
Vega Lite Scatter Plot 00:00:00
Create Altair Line Chart 00:00:00
Create Altair Line Plot 00:00:00
Create Altair Scatter Plot 00:00:00
Create Altair Area Chart 00:00:00
Create Altair Scatter Matrix 00:00:00
Scatter With Links [ Exercise] 00:00:00
Create Altair Heatmap [Exercise] 00:00:00
Create Horizontal Altair Bar Plot [Exercise] 00:00:00
Set Theme 00:00:00
Build An Altair Grouped Bar Chart 00:00:00
Stack The Altair Bar Chart [Exercise] 00:00:00
Normalized Stacked Bar Chart [Exercise 00:00:00
Add Text To The Chart 00:00:00
Add Altair Boxplot 00:00:00
Create An Interactive Legend In Altair 00:00:00
Concatenate Charts 00:00:00
Create Dual Y Axis In Altair 00:00:00
Horizontal Concatenation [Exercise] 00:00:00
Vertical Concatenation [Exercise] 00:00:00
Interactive Chart 00:00:00
Section 17 - Streamlit Layout
Laying Out Your Application 00:00:00
Add Interactivity – Date Inputs 00:00:00
Add Interactivity – Input Box 00:00:00
Add Interactivity – Drop Down [Exercise] 00:00:00
Add Interactivity – Select Slider [Exercise] 00:00:00
Add Interactivity – Select Box 00:00:00
Add Interactivity – Button 00:00:00
Section 18 - Natural Language Processing
Section Introduction 00:00:00
Sentiment Analysis 00:00:00
Create A Question Answering App 00:00:00
Generate Text [Exercise] 00:00:00
Named Entity Recognition[Exercise] 00:00:00
Summarize Text 00:00:00
Translate Text [Exercise] 00:00:00
Section 19 - Deploy Streamlit Application
Section Introduction 00:00:00
Streamlit Sharing 00:00:00
Heroku 00:00:00
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