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Snehan Kekre
Welcome to this hands-on project on building your first interactive, data dashboard 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 dashboards and web apps, all with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 150 lines of Python code!
Prior experience with writing simple Python scripts and using pandas for data manipulation is recommended.
Read more
Welcome to this hands-on project on building your first interactive, data dashboard 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 dashboards and web apps, all with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 150 lines of Python code!
Prior experience with writing simple Python scripts and using pandas for data manipulation is recommended.
Read more
Welcome to this hands-on project on building your first interactive, data dashboard 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 dashboards and web apps, all with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 150 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.
Register for this course and see more details by visiting:
OpenCourser.com/course/9wfjqa/create
What's inside
Syllabus
Create Interactive Dashboards with Streamlit and Python
Welcome to this hands-on project on building your first interactive, data dashboard 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 dashboards and web apps, all with zero web development experience! We are going to load, explore, visualize and interact with data, and generate dashboards in less than 150 lines of Python code!
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds foundational skills in data manipulation and visualization using Python and Streamlit
Specifically designed for beginners with no prior web development experience
Enhances data science skills with practical hands-on project
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Save Create Interactive Dashboards with Streamlit and Python to your list so you can find it easily later:
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Reviews summary
Streamlit interactive dashboards
Learners say that Streamlit Interactive Dashboards is an excellent course that provides a great introduction to Streamlit. The course is well-paced and engaging, and the instructor is clear and easy to understand. Students appreciate the hands-on approach of the course, which allows them to learn by doing. Additionally, learners say that the course is a great way to build a portfolio of interactive dashboards.
Very straightforward and informative! :)
"Very straightforward and informative! :)"
"Very usefull mini course."
"A nice project to enhance programming skill"
Great experience of hands on practice.
"Great experience of hands on practice."
"Es genial aprender haciendo."
"I really enjoyed the project. It is completely guided so it is basically like following a tutorial, but the instructor gives enough and meaningful insight into the concepts."
The course is very clear and interesting.
"The course is very clear and interesting."
"Instructions was crystal clear to make me complete the coding along with the instructor."
"Um projeto simples porém muito completo que permitiu aprende diversos componentes do Streamlit, recomendo."
Instructor is fantastic.
"Top class stuff.Instructor is fantastic."
"The instructor has a very good technique to teach."
"Teaching was great just straight to the point not dragging."
The font size in the cloud desktop is very small.
"The font size in the cloud desktop is very small."
The Rhyme platform is very buggy.
"The Rhyme platform is very buggy."
"short-cuts like Ctrl+c and Ctrl+v are not mapped appropriately, so you can't use them."
Too much hand holding.
"Too much hand holding."
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 Create Interactive Dashboards with Streamlit and Python with these
activities:
Review Pandas documentation
Show steps
Refresh your knowledge of Pandas functions and methods by reviewing the official documentation.
View
Python for Data Analysis
on Amazon
Show steps
-
Read the Pandas User Guide.
-
Identify key concepts and functions.
-
Practice using the functions in your own Python scripts.
Read 'Effective Data Visualization' by Stephen Few
Show steps
Expand your knowledge of effective data visualization principles and best practices by reading this influential book.
View
Information Dashboard Design: Displaying Data...
on Amazon
Show steps
-
Read the book and make notes.
-
Apply the principles to your own data visualization projects.
-
Discuss the book's ideas with other students or colleagues.
Solve Python coding challenges
Show steps
Complete coding challenges to strengthen your understanding of Python and improve your problem-solving skills.
Browse courses on
Python
Show steps
-
Find Python coding challenges online or in books.
-
Attempt to solve the challenges independently.
-
Review your solutions and identify areas for improvement.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice data visualization techniques
Show steps
Enhance your ability to visualize data by exploring various techniques and creating your own visualizations.
Browse courses on
Data Visualization
Show steps
-
Research different data visualization techniques.
-
Create a dataset or find one online.
-
Use Python libraries (e.g., Matplotlib, Seaborn) to create visualizations.
-
Experiment with different visualization types and styles.
Join a study group or attend a hackathon
Show steps
Collaborate with others to reinforce learning, exchange perspectives, and solve problems together.
Show steps
-
Find a study group or hackathon that aligns with your interests.
-
Participate actively in discussions and activities.
-
Contribute your knowledge and skills to the group.
Create a resource list on data science tools and libraries
Show steps
Consolidate your knowledge and help others by compiling a comprehensive list of useful resources.
Browse courses on
Data Science
Show steps
-
Research and identify relevant data science tools and libraries.
-
Categorize the resources based on their functionality or purpose.
-
Include brief descriptions and links to documentation or tutorials.
-
Share your resource list with others in the field.
Build a simple dashboard with Streamlit
Show steps
Reinforce your understanding of dashboard creation by building your own interactive dashboard with Streamlit.
Browse courses on
Streamlit
Show steps
-
Choose a dataset to visualize.
-
Create a Streamlit app.
-
Load and explore the dataset.
-
Create visualizations to display the data.
-
Deploy your dashboard and share it with others.
Design a data visualization dashboard
Show steps
Solidify your understanding of dashboard design by creating a comprehensive data visualization dashboard.
Browse courses on
Data Visualization
Show steps
-
Define the purpose and target audience of your dashboard.
-
Gather and clean the necessary data.
-
Choose appropriate visualizations and arrange them effectively.
-
Incorporate interactive elements to enhance user engagement.
-
Present your dashboard to others and gather feedback.
Participate in a data science competition
Show steps
Challenge yourself by applying your skills to real-world problems and competing against others.
Browse courses on
Data Science
Show steps
-
Identify a relevant data science competition.
-
Form a team or work independently.
-
Analyze the problem statement and gather data.
-
Develop and implement a solution.
-
Submit your solution and evaluate your results.
Review Pandas documentation
Show steps
Refresh your knowledge of Pandas functions and methods by reviewing the official documentation.
View
Python for Data Analysis
on Amazon
Show steps
Show steps
Show steps
- Read the Pandas User Guide.
- Identify key concepts and functions.
- Practice using the functions in your own Python scripts.
Read 'Effective Data Visualization' by Stephen Few
Show steps
Expand your knowledge of effective data visualization principles and best practices by reading this influential book.
View
Information Dashboard Design: Displaying Data...
on Amazon
Show steps
Show steps
Show steps
- Read the book and make notes.
- Apply the principles to your own data visualization projects.
- Discuss the book's ideas with other students or colleagues.
Solve Python coding challenges
Show steps
Complete coding challenges to strengthen your understanding of Python and improve your problem-solving skills.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find Python coding challenges online or in books.
- Attempt to solve the challenges independently.
- Review your solutions and identify areas for improvement.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice data visualization techniques
Show steps
Enhance your ability to visualize data by exploring various techniques and creating your own visualizations.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Research different data visualization techniques.
- Create a dataset or find one online.
- Use Python libraries (e.g., Matplotlib, Seaborn) to create visualizations.
- Experiment with different visualization types and styles.
Join a study group or attend a hackathon
Show steps
Collaborate with others to reinforce learning, exchange perspectives, and solve problems together.
Show steps
Show steps
Show steps
- Find a study group or hackathon that aligns with your interests.
- Participate actively in discussions and activities.
- Contribute your knowledge and skills to the group.
Create a resource list on data science tools and libraries
Show steps
Consolidate your knowledge and help others by compiling a comprehensive list of useful resources.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Research and identify relevant data science tools and libraries.
- Categorize the resources based on their functionality or purpose.
- Include brief descriptions and links to documentation or tutorials.
- Share your resource list with others in the field.
Build a simple dashboard with Streamlit
Show steps
Reinforce your understanding of dashboard creation by building your own interactive dashboard with Streamlit.
Browse courses on
Streamlit
Show steps
Show steps
Show steps
- Choose a dataset to visualize.
- Create a Streamlit app.
- Load and explore the dataset.
- Create visualizations to display the data.
- Deploy your dashboard and share it with others.
Design a data visualization dashboard
Show steps
Solidify your understanding of dashboard design by creating a comprehensive data visualization dashboard.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Define the purpose and target audience of your dashboard.
- Gather and clean the necessary data.
- Choose appropriate visualizations and arrange them effectively.
- Incorporate interactive elements to enhance user engagement.
- Present your dashboard to others and gather feedback.
Participate in a data science competition
Show steps
Challenge yourself by applying your skills to real-world problems and competing against others.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Identify a relevant data science competition.
- Form a team or work independently.
- Analyze the problem statement and gather data.
- Develop and implement a solution.
- Submit your solution and evaluate your results.
Career center
Learners who complete Create Interactive Dashboards with Streamlit and Python will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their skills in programming, statistics, and data visualization to make sense of large amounts of data for businesses of all sizes. With the ability to build interactive dashboards and web apps with Streamlit, you can build dashboards designed to increase efficiency and productivity of teams in any industry.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, analyzing, and interpreting data to help businesses make better decisions. The ability to visualize and interact with data using Streamlit can help you present your findings in a clear and concise way, making you a more effective Data Scientist.
Business Analyst
Business Analyst
Business Analysts use data to identify problems and opportunities within a business. The ability to build interactive dashboards with Streamlit helps to visualize complex data and communicate findings to stakeholders, making you a more effective Business Analyst.
Software Developer
Software Developer
Software Developers design, develop, and maintain software systems. The ability to build interactive web apps with Streamlit can help you create more user-friendly and engaging software applications, making you a more effective Software Developer.
Web Developer
Web Developer
Web Developers design and develop websites and web applications. The ability to build interactive dashboards and web apps with Streamlit can help you create more visually appealing and interactive web experiences, making you a more effective Web Developer.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists are responsible for creating visual representations of data to help businesses understand their data. The ability to build interactive dashboards with Streamlit can help you create more engaging and informative data visualizations, making you a more effective Data Visualization Specialist.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. The ability to build interactive dashboards with Streamlit can help you communicate your findings in a clear and concise way, making you a more effective Business Intelligence Analyst.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and improve marketing campaigns. The ability to build interactive dashboards with Streamlit can help you visualize complex data and communicate your findings to stakeholders, making you a more effective Marketing Analyst.
Financial Analyst
Financial Analyst
Financial Analysts use data to evaluate investments and make financial recommendations. The ability to build interactive dashboards with Streamlit can help you visualize complex financial data and communicate your findings to stakeholders, making you a more effective Financial Analyst.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. The ability to build interactive dashboards with Streamlit can help you track product performance and make data-driven decisions, making you a more effective Product Manager.
Entrepreneur
Entrepreneur
Entrepreneurs start and run their own businesses. The ability to build interactive dashboards with Streamlit can help you track your business performance and make data-driven decisions, making you a more successful Entrepreneur.
Consultant
Consultant
Consultants provide advice and guidance to businesses on a variety of topics. The ability to build interactive dashboards with Streamlit can help you communicate your findings in a clear and concise way, making you a more effective Consultant.
Teacher
Teacher
Teachers educate students in a variety of subjects. The ability to build interactive dashboards with Streamlit can help you create more engaging and interactive lesson plans, making you a more effective Teacher.
Writer
Writer
Writers create written content for a variety of purposes. The ability to build interactive dashboards with Streamlit can help you visualize your data and communicate your findings in a clear and concise way, making you a more effective Writer.
Artist
Artist
Artists create visual art for a variety of purposes. The ability to build interactive dashboards with Streamlit can help you visualize your data and communicate your findings in a clear and concise way, making you a more effective Artist.
For more career information including salaries, visit:
OpenCourser.com/course/9wfjqa/create
Reading list
We've selected 14 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
Create Interactive Dashboards with Streamlit and Python.
Comprehensive guide to data visualization using Python and JavaScript. It covers a wide range of topics, from data exploration and visualization to interactive web-based visualizations. This book valuable resource for anyone who wants to learn how to create interactive data visualizations.
Practical guide to creating interactive data visualizations for the web. It covers a wide range of topics, from data visualization basics to advanced techniques for creating interactive visualizations. This book valuable resource for anyone who wants to learn how to create interactive data visualizations for the web.
Comprehensive guide to using Python for data analysis. It covers everything from the basics of Python to advanced topics like machine learning and data mining.
Comprehensive guide to machine learning using Python. It covers a wide range of topics, from machine learning basics to advanced techniques for building machine learning models. This book valuable resource for anyone who wants to learn machine learning using Python.
Comprehensive guide to deep learning using Python. It covers a wide range of topics, from deep learning basics to advanced techniques for building deep learning models. This book valuable resource for anyone who wants to learn deep learning using Python.
Practical guide to using Pandas, a Python library for data manipulation and analysis. It covers everything from the basics of Pandas to advanced topics like data wrangling and data visualization.
Comprehensive guide to natural language processing using Python. It covers a wide range of topics, from natural language processing basics to advanced techniques for building natural language processing models. This book valuable resource for anyone who wants to learn natural language processing using Python.
Comprehensive guide to data structures and algorithms in Python. It covers a wide range of topics, from data structures basics to advanced algorithms for solving complex problems. This book valuable resource for anyone who wants to learn data structures and algorithms in Python.
Comprehensive guide to Python for beginners. It covers a wide range of topics, from Python basics to advanced techniques for building Python programs. This book valuable resource for anyone who wants to learn Python.
Save
Practical guide to using Python for data visualization. It covers a wide range of topics, from basic charts and graphs to more advanced topics like geospatial visualization and machine learning.
Comprehensive guide to database systems. It covers a wide range of topics, from database systems basics to advanced techniques for building database systems. This book valuable resource for anyone who wants to learn database systems.
Save
Comprehensive guide to operating systems. It covers a wide range of topics, from operating systems basics to advanced techniques for building operating systems. This book valuable resource for anyone who wants to learn operating systems.
Save
Comprehensive guide to computer networks. It covers a wide range of topics, from computer networks basics to advanced techniques for building computer networks. This book valuable resource for anyone who wants to learn computer networks.
Comprehensive guide to using Python for data science. It covers everything from the basics of Python to advanced topics like machine learning and data mining.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9wfjqa/create
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Effort
2 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Snehan Kekre
Language
English
Good to know
Builds foundational skills in data manipulation and visualization using Python and Streamlit
Specifically designed for beginners with no prior web development experience
Enhances data science skills with practical hands-on project
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