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