Build Interactive Sales Dashboards with Python and Dash

In this course, you will learn how to create interactive dashboards using Dash, Plotly, and Python, from the fundamentals to a fully functional professional application. Dash is a Python library created by Plotly that allows developers to build web applications for data analysis without writing any JavaScript code, making it ideal for data analysts, data engineers, and data scientists.

You’ll start by setting up your dependencies and configuring your environment, understanding when to use Dash compared to tools like Streamlit or Power BI. You’ll learn to create your first base project and the fundamental structure of a Dash application, using components like html.Div, dcc.Graph, dcc.Dropdown, and dcc.DatePickerRange. Afterward, you’ll explore data loading and preprocessing with Pandas: cleaning, normalization, creating derived columns for KPIs, and storage in CSV or MySQL.

Next, you’ll design your dashboard layout, organizing header sections, filters, KPIs, and charts, and customizing styles with CSS or Bootstrap. You’ll delve into callbacks, the heart of Dash, connecting filters and dynamic charts. Implement visualizations with bar graphs, line charts, treemaps, and interactive maps, as well as summary tables and real-time updatable KPIs. Finally, you’ll review your complete project, enhance user experience, export models, and prepare your dashboard for local execution or deployment in production environments. This course combines theory, guided practice, and real-world examples, equipping you with the skills to build interactive analytical applications using Dash and Plotly, integrating databases, real-time data, and advanced visualizations.

What you will learn:

• Understand what Dash is and when to use it over tools like Streamlit or Power BI.
• Create interactive web applications from scratch using Python, Dash, and Plotly.
• Connect and process data from CSV, Excel, or MySQL databases.
• Design professional dashboards with layouts, filters, and dynamic callbacks.
• Create advanced visualizations: charts, KPI tables, treemaps, and geographical maps.
• Deploy and optimize a complete application ready for production.

Course Content:

• Sections: 8
• Lectures: 37
• Duration: 3h 44m

Requirements:

• Basic knowledge of Python and data manipulation with Pandas.
• Install Python 3.9 or higher.
• Internet connection to install dependencies (Dash, Plotly, SQLAlchemy, MySQLClient).
• No prior experience in web development required.
• Course accessible for analysts and programmers wishing to create professional web dashboards.

Who is it for?

• Data analysts wanting to create interactive dashboards with Python.
• Developers looking to learn Dash and Plotly for analytical web applications.
• BI professionals looking to automate reporting and connect databases.
• Students or self-learners interested in developing data-driven applications.

What are you waiting for to get started?

Enroll today and take your skills to the next level. Coupons are limited and may expire at any time!

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