Build a real, deployed data dashboard in 5 days — interactive charts with Plotly, database connections with SQL, a multi-page Streamlit app, and AI-powered natural language queries so anyone can ask questions about your data.
This is a text-first course that links out to the best supporting material on the internet instead of trying to replace it. The goal is to make this the best course on data dashboard you can find — even without producing a single minute of custom video.
You build a single dashboard application across all 5 days — adding charts, SQL connections, multiple pages, and AI queries progressively.
Streamlit is the fastest way to go from Python script to interactive web app. This course explains why it's the right choice for data dashboards.
Day 5 adds natural language queries with Claude — type a question in English, get a chart and analysis. The feature that impresses every stakeholder.
Each day is designed to finish in about an hour of focused reading plus hands-on coding. No live classes, no quizzes.
Each day stands alone. Read them in order for the full picture, or jump straight to the day that answers the question you have today.
Streamlit setup, running your first app, layout components, sidebar, text and metric displays. Your first working dashboard page.
Bar charts, line charts, scatter plots, and maps with Plotly Express. Connecting charts to real data files. Making charts interactive.
Connecting Streamlit to SQLite or PostgreSQL, querying data into pandas DataFrames, and building charts from live database queries.
Streamlit multi-page apps, navigation, shared state between pages, and the app architecture that scales beyond a single page.
Adding a natural language query interface with Claude — users type questions in English, Claude generates SQL or analysis, results display as charts.
Instead of shooting our own videos, we link to the best deep-dives already on YouTube. Watch them alongside the course. All external, all free, all from builders who ship this stuff.
Getting started with Streamlit — from your first app to multi-page dashboards with real data.
Building interactive data visualizations with Plotly Express — bar charts, line charts, scatter plots, and maps.
Connecting Streamlit applications to databases — SQLite, PostgreSQL, and building dashboards from live query results.
AI-powered natural language query interfaces — how to convert plain English questions into SQL and display the results.
Best practices for data dashboard design — what to show, how to organize it, and what makes dashboards stakeholders actually use.
Deploying Streamlit apps to Streamlit Community Cloud, Railway, or other platforms — from local to live.
The best way to go deeper on any topic is to read canonical open-source implementations. These repositories implement the core patterns covered in this course.
Streamlit — the Python framework this course uses for building data apps. Well-documented with excellent examples in the source.
Plotly's Python library — the interactive charting library this course uses for all visualizations.
pandas — the data manipulation library that connects database queries to Plotly charts in every Streamlit dashboard.
The Claude Python SDK — used in Day 5 to add natural language query capabilities to the dashboard.
You can write SQL and work with data but want to turn your analysis into a live, shareable dashboard. This course is the direct path.
Your team needs a data tool. Streamlit lets you build it fast without frontend development skills — this course shows you how.
You use Excel for data analysis and want to build interactive dashboards. This course uses Python but explains each step clearly.
The 2-day in-person Precision AI Academy bootcamp covers data analytics, dashboards, and AI-powered analysis — hands-on with Bo. 5 U.S. cities. $1,490. 40 seats max. June–October 2026 (Thu–Fri).
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