How can you use web scraping to collect and visualize dam water levels more efficiently? In this 1-on-1 course, you’ll learn how to extract data from websites, store it in a spatial database, and display it on interactive maps. With expert guidance and hands-on assignments, you’ll master web scraping and data analysis techniques you can apply right away.
Web scraping is a fast, automated way to collect data from websites. It’s especially useful for tracking dam water levels, where up-to-date insights are critical. With web scraping, you can pull real-time data, process it, and visualize it—no manual searching required.
Python makes this process simple and powerful. You’ll use it to extract, clean, and analyze data with tools like BeautifulSoup and Pandas—two of the most popular libraries for data handling. That’s why Python is a go-to choice for professionals working in water management, GIS, and data analysis.
By automating data collection and visualization, you can quickly generate insights and support smarter decision-making.
In this course, you’ll learn how to collect dam level data from websites using web scraping and Python. You’ll start by building a data model and plotting the results on an interactive map using Folium.
Next, you’ll explore how to use Django’s Template Engine to display updated data on your website—without needing Ajax. This makes it easy to create dynamic pages that automatically reflect the latest information.
You’ll also set up a spatial database using PostgreSQL, commonly used for geospatial data. On top of your map, you’ll add a floating dashboard with charts that visualize trends and patterns in water levels.
Blended learning gives you the best of both worlds—live instruction and self-paced modules—so you can build real, job-ready skills. In this course, you’ll learn how to gather, process, and visualize dam level data using Python, PostgreSQL, and Django.
We kick things off with a live session where you’ll dive right into real data. With help from experts, you’ll scrape dam levels from websites, load them into a spatial database, and get your data ready for mapping.
Then, in our self-paced modules, you’ll learn key concepts step by step. You’ll explore Python libraries like BeautifulSoup and Pandas, build your database in PostgreSQL/PostGIS, and create interactive maps using Leaflet and Django.
Later, in a second live session, you’ll put everything together. You’ll build a mini dashboard that shows charts and real-time data, and connect your backend to the frontend using Django templates.
A highlight of this course is its real-world workflow. You’ll work through practical water management scenarios and build tools you can use in your own projects right away.
By the end of the course, you won’t just understand the theory—you’ll be able to collect, manage, and visualize data that supports smarter, faster decisions in your field.
After completing this course, you’ll be able to:
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
