Streamlit Bootcamp

Streamlit Bootcamp, available at $74.99, has an average rating of 4.3, with 29 lectures, based on 189 reviews, and has 25372 subscribers.

You will learn about Building complete Web Applications from Scratch using Streamlit. Develop Strong Skills about ALL Streamlit's Basic and Advanced Features. Use Streamlit to create Data Science and Machine Learning Web Apps. Learn to build beautiful User Interface for your ML models using Streamlit. This course is ideal for individuals who are Python Developers curious about Streamlit. or Data Scientists and ML Engineers who want to create a quick and beautiful user interface for their ML Models. or Anyone who wants to learn to build web apps in a fast and easy manner. It is particularly useful for Python Developers curious about Streamlit. or Data Scientists and ML Engineers who want to create a quick and beautiful user interface for their ML Models. or Anyone who wants to learn to build web apps in a fast and easy manner.

Enroll now: Streamlit Bootcamp

Summary

Title: Streamlit Bootcamp

Price: $74.99

Average Rating: 4.3

Number of Lectures: 29

Number of Published Lectures: 29

Number of Curriculum Items: 29

Number of Published Curriculum Objects: 29

Original Price: ₹3,999

Quality Status: approved

Status: Live

What You Will Learn

Building complete Web Applications from Scratch using Streamlit.
Develop Strong Skills about ALL Streamlit's Basic and Advanced Features.
Use Streamlit to create Data Science and Machine Learning Web Apps.
Learn to build beautiful User Interface for your ML models using Streamlit.

Who Should Attend

Python Developers curious about Streamlit.
Data Scientists and ML Engineers who want to create a quick and beautiful user interface for their ML Models.
Anyone who wants to learn to build web apps in a fast and easy manner.

Target Audiences

Python Developers curious about Streamlit.
Data Scientists and ML Engineers who want to create a quick and beautiful user interface for their ML Models.
Anyone who wants to learn to build web apps in a fast and easy manner.

ARE YOU LOOKING A FAST AND EASY WAY TO CREATE WEB APPS AND DASHBOARDS FOR YOUR DATA SCIENCE AND MACHINE LEARNING PROJECTS THEN THIS IS THE PERFECT COURSE FOR YOU.

Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science that can be used to share analytics results, build complex interactive experiences, and illustrate new machine learning models. In just a few minutes you can build and deploy powerful data apps.

On top of that, developing and deploying Streamlit apps is incredibly fast and flexible, often turning application development time from days into hours.

In this course you will learn:

Different input types in streamlit
Data display elements
Layouts and Containers
How to add images and videos to your Streamlit web app
Different Chart elements like Line Chart, Bar Chart etc…
3 Complete Projects using Machine Learning and Streamlit.
Stock Market Index Prediction App
Calories Burned Calculator App
Insurance Premium Prediction App

At the end of the course, you will have built several applications that you can include in your Data Science and Machine Learning portfolio. You will also have a new skill to add to your resume.

After completing this course you will be able to quickly build web apps and dashboards for your Data Science and Machine Learning Projects using Streamlit.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction and Welcome

Lecture 2: Course Overview and Key Learning Outcomes

Lecture 3: Installation and Setup

Chapter 2: Text Elements in Streamlit

Lecture 1: Different type of Text Elements

Chapter 3: Data Display Elements in Streamlit

Lecture 1: Working with DataFrames

Lecture 2: Tables in Streamlit

Lecture 3: JSON in streamlit

Chapter 4: Chart Elements in Streamlit

Lecture 1: Line Chart

Lecture 2: Area Chart

Lecture 3: Bar Chart

Lecture 4: Pyplot

Chapter 5: Input Widgets in Streamlit

Lecture 1: Buttons

Lecture 2: Download Button

Lecture 3: Check Box

Lecture 4: Radio Button

Lecture 5: Select Box

Lecture 6: Slider

Lecture 7: Text Input

Lecture 8: Number Input

Lecture 9: Date Input

Chapter 6: Media Items in Streamlit

Lecture 1: Working with Images

Lecture 2: Working with Videos

Chapter 7: Layouts and Containers in Streamlit

Lecture 1: Sidebar

Lecture 2: Columns

Lecture 3: Expander

Chapter 8: Projects

Lecture 1: Insurance Premium Predictor App

Lecture 2: Calories Burned Calculator App Part One

Lecture 3: Calories Burned Calculator App Part Two

Lecture 4: Stock Market Index Prediction App

Instructors

Raj Chhabria
Computer Science Engineer with Specialization in DataScience

Rating Distribution

1 stars: 2 votes
2 stars: 6 votes
3 stars: 29 votes
4 stars: 65 votes
5 stars: 87 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu