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Build a Data Science Web App with Streamlit and Python

Welcome to this hands-on project on building your first data science web app with the Streamlit library in Python. By the end of this project, you are going to be comfortable with using Python and Streamlit to build beautiful and interactive web apps with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 100 lines of Python code!

Prior experience with writing simple Python scripts and using pandas for data manipulation is recommended.

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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What's inside

Syllabus

Build a Data Science Web App with Streamlit and Python

Welcome to this hands-on project on building your first data science web app with the Streamlit library in Python. By the end of this project, you are going to get comfortable with using Python and Streamlit to build beautiful and interactive web apps with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 100 lines of Python code!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces commonly-used Python library Streamlit for the creation of data science web applications

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Reviews summary

Beginner-friendly streamlit crash course

Learners say this beginner-friendly course provides a hugely positive introduction to Streamlit. With very little code, you'll be able to build interactive web apps using Python, Pandas, and Numpy. The course uses the Rhyme platform, which allows you to run code in the cloud. While Rhyme is convenient, some learners complain about its lag and connectivity issues. Despite this, many learners recommend this course for its clear explanations, engaging instructor, and practical project.

Clear, engaging, knowledgeable

"The instructor has provided all the information needed and had an engaging informative session and extremely happy that I enrolled for this guided project."

"The instructor has done a great job explaining things."

"The instructor is pretty clear and goes straight to the point. You can see that he knows the subject and gives enough explanation without going too deep on unnecesary details."

Provides a practical project to apply Streamlit skills

"Excellent project and hands on course to get started with streamlit and create a beautiful interactive web app."

"Hands-on Experience is always the best way to build the project."

"The project is explained clear and a nice workout."

Suitable for those with little to no coding experience

"Excellent course for beginners as well as experienced researchers from other fields"

"Great for an explanatory walkthrough into the Streamlit library and its uses in Python."

"Very straight to the point which I appreciated."

Some learners express concerns about code quality

"You can learn a lot on this, but mostly from fixing the bad code and bad practice."

"don't waste your moneygo work through the examples in the streamlit documentation instead"

Convenient, but laggy and prone to connectivity issues

"But Rhyme ( the VM software) was just too slow and laggy."

"Rhyme platform for teaching, but seriously from now onwards I hate this Rhyme"

"Such a creep place where you will stick without any reason, and there is no place for your help"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Build a Data Science Web App with Streamlit and Python with these activities:

Read 'Introduction to Data Science in Python'

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Expand your knowledge of data science and Python by reading this introductory book.

View Working with Network Data on Amazon

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Read the book and take notes.
Complete the exercises and projects in the book.

Review basic Python

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Review the fundamentals of Python to ensure you have a strong foundation for this course.

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Review Python syntax and data structures.
Solve simple Python coding exercises.

Explore the Streamlit documentation

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Become familiar with the Streamlit library by exploring its documentation and examples.

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Visit the official Streamlit documentation.
Review the Streamlit gallery of examples.

Nine other activities

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Solve Streamlit coding challenges

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Reinforce your understanding of Streamlit by solving coding challenges and building simple web apps.

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Find Streamlit coding challenges online.
Create a simple Streamlit web app to visualize a dataset.

Explore Streamlit's documentation and tutorials

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Streamlit's documentation and tutorials will provide you with a solid foundation in using the library and building web apps with Python.

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Visit the Streamlit documentation website
Read through the Streamlit tutorial
Follow along with the examples provided in the tutorial

Answer questions on a Streamlit forum

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Answering questions on a Streamlit forum will help you solidify your understanding of the library and help others learn.

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Join a Streamlit forum
Answer questions posted by other users

Join a Streamlit study group

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Connect with other learners and share knowledge by joining a Streamlit study group.

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Find a Streamlit study group online or in your local area.
Participate in group discussions and share your experiences.

Build a simple data visualization web app

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Building a simple data visualization web app will help you apply the concepts you learn in the course and reinforce your understanding of Streamlit.

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Choose a dataset to visualize
Create a Streamlit app to visualize the data
Deploy your app online

Participate in a Streamlit hackathon

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Participating in a Streamlit hackathon will give you the opportunity to work on a project with others and showcase your skills.

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Find a Streamlit hackathon to participate in
Form a team or work on your own
Develop a Streamlit app
Submit your app to the hackathon

Build a Streamlit dashboard

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Demonstrate your proficiency in Streamlit by building a dashboard that visualizes and interacts with data.

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Choose a dataset to visualize.
Create a Streamlit dashboard to display the data.
Deploy the dashboard to a hosting platform.

Develop a data science web app for a specific use case

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Developing a data science web app for a specific use case will challenge you to apply your skills and knowledge to a real-world problem.

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Identify a specific use case for your web app
Design and develop the app
Deploy your app online
Share your app with others

Contribute to the Streamlit community

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Deepen your understanding of Streamlit by contributing to its open-source codebase.

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Find a Streamlit project on GitHub.
Submit a bug report or feature request.
Contribute code to the project.

Career center

Learners who complete Build a Data Science Web App with Streamlit and Python will develop knowledge and skills that may be useful to these careers:

Data Visualization Specialist

Data Visualization Specialists create visualizations that communicate data insights to a variety of audiences. This course on building web apps with Streamlit may be useful to Data Visualization Specialists, as it can help them to create more interactive and engaging visualizations.

See salaries and explore the career path for Data Visualization Specialist

Machine Learning Engineer

Machine Learning Engineers design and implement machine learning models, which can be used to automate tasks, make predictions, and provide insights from data. This course on building web apps with Streamlit can be useful to Machine Learning Engineers, as they may use these skills to create interactive interfaces for their models, allowing users to easily interact with and experiment with them.

See salaries and explore the career path for Machine Learning Engineer

UX Designer

UX Designers are responsible for the design of user interfaces for websites and applications. This course on building web apps with Streamlit may be useful to UX Designers, as it can help them to create more interactive and engaging user interfaces.

See salaries and explore the career path for UX Designer

Software Engineer

Software Engineers design, develop, and maintain software applications. This course on building web apps with Streamlit may be useful to Software Engineers, as it can help them to build more interactive and engaging user interfaces for their software applications.

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Web Developer

Web Developers design and develop websites and web applications. This course on building web apps with Streamlit may be useful to Web Developers, as it can help them to build more interactive and engaging web applications.

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Product Manager

Product Managers are responsible for the development and launch of new products and features. This course on building web apps with Streamlit may be useful to Product Managers, as it can help them to create interactive prototypes and demos of their products, and to get feedback from users.

See salaries and explore the career path for Product Manager

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns, and to provide insights that can help businesses make better decisions. This course on building web apps with Streamlit can be useful to Data Analysts, as they may use these skills to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

See salaries and explore the career path for Data Analyst

Data Engineer

Data Engineers build and maintain the infrastructure that is used to store and process data, and they develop the tools and processes that are used to manage and analyze data. This course on building web apps with Streamlit may be useful to Data Engineers, as they may use these skills to create interactive interfaces for their data management and analysis tools.

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Business Analyst

Business Analysts use data to identify business problems and opportunities, and to develop solutions that can help businesses improve their performance. This course on building web apps with Streamlit may be useful to Business Analysts, as they may use these skills to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

See salaries and explore the career path for Business Analyst

Risk Analyst

Risk Analysts identify and assess risks to businesses and organizations. This course on building web apps with Streamlit may be useful to Risk Analysts, as it can help them to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

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Data Scientist

Data Scientists build and maintain comprehensive databases, and use them for advanced statistical modeling and analysis in order to support the decision-making of their employer or clients. Those working in this career role may use Streamlit to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights. The skills and knowledge learned in this course may therefore be useful to a Data Scientist.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians collect, analyze, and interpret data to provide insights and make predictions. This course on building web apps with Streamlit may be useful to Statisticians, as it can help them to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

See salaries and explore the career path for Statistician

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. This course on building web apps with Streamlit may be useful to Operations Research Analysts, as it can help them to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course on building web apps with Streamlit may be useful to Quantitative Analysts, as it can help them to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts analyze financial data to make investment recommendations and provide advice to businesses and individuals. This course on building web apps with Streamlit may be useful to Financial Analysts, as it can help them to create interactive visualizations and dashboards, making it easy to explore and interact with data, and generate insights.

See salaries and explore the career path for Financial Analyst

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Build a Data Science Web App with Streamlit and Python.

Interactive Data Visualization for the Web

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Provides a comprehensive overview of the techniques and tools used to create interactive data visualizations for the web. It covers everything from data preparation and cleaning to creating visualizations and dashboards using popular libraries such as D3.js and Plotly.

Build a Data Science Web App with Streamlit and Python

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Beginner-friendly streamlit crash course

Activities

Career center

Reading list

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