Total study time: 24 hours
How can you teach a computer to recognize objects in an image? In this one-on-one course, you’ll explore the power of OpenCV in Python and learn how to analyze images and apply smart algorithms with just a few lines of code. With personal guidance and interactive assignments, you’ll build practical applications you can use right away.
OpenCV—short for Open Source Computer Vision Library—is a powerful, free software library used around the world for image processing and computer vision. From facial recognition and object detection to real-time video editing, OpenCV powers technologies found in everyday tools like smartphones, drones, and security systems.
One reason OpenCV is so accessible is its seamless integration with Python. Python is clean, easy to learn, and ideal for rapid prototyping. Whether you’re new to coding or already have some experience, it’s the perfect language for analyzing and automating visual data.
Together, OpenCV and Python allow you to analyze images and videos, detect objects, and automate visual tasks with minimal code. Plus, this technology is highly versatile—used in fields from industrial quality control to geospatial analysis.
In short, OpenCV with Python gives you a powerful, approachable way to get started with computer vision—and that’s exactly what this blended learning course is designed to help you do.
This course is for anyone ready to bridge the gap between image processing and coding. Maybe you know a bit about visual data but haven’t coded before, or perhaps you’re a developer curious about working with images. Either way, you’ll learn to use Python and OpenCV to turn raw visuals into smart, automated workflows.
You’ll begin with the basics: understanding how digital images are structured and how to analyze them. From there, you’ll explore editing techniques and translate them into working Python code. You’ll manipulate images, detect objects, and apply simple algorithms to process patterns automatically.
Next, you’ll get hands-on with Python—an ideal language for image processing, especially when paired with OpenCV. Step by step, you’ll write scripts, fine-tune parameters, and improve your results. By the end, you’ll be building your own applications and understanding how more advanced tools—like facial recognition and filter effects—actually work.
Blended learning gives you the best of both worlds—live interaction and flexible, self-paced study—so you can build real, job-ready skills in computer vision and image analysis.
We kick things off with a live session where you’ll dive into image editing and detection using OpenCV. With guidance from experienced instructors, you’ll write your first scripts and start building basic tools—all using real images and Python code.
Then, through our self-paced modules, you’ll deepen your skills on your own schedule. You’ll explore topics like color spaces, filters, and object tracking. Along the way, you’ll test your code on real datasets and learn how to adjust your workflows for better performance.
Later, in a second live session, you’ll bring it all together. You’ll work on practical coding challenges, refine your techniques, and receive personalized feedback to sharpen your approach.
A highlight of the course is its case-based structure. You’ll build useful outputs—like detection scripts and annotated visuals—that can be directly applied in fields like remote sensing, geospatial mapping, or inspection systems.
By combining expert-led sessions with flexible learning, this course helps you move beyond theory. By the end, you’ll be confidently processing visual data and turning it into insights that support smarter, faster decisions—no matter your industry.
After completing this course, you will 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.
We aim to make our courses accessible to as many people as possible. If the course fee is a concern, instead of registering directly, you can indicate on the registration form that you’d like to receive a quote tailored to your needs. In many cases, we can offer flexible solutions. For instance, we can adjust the course content for large groups, shorten the course based on existing knowledge, or offer daily rates to suit your requirements.
Yes, you can reach out to the instructor with questions for up to 2 weeks after the course. Since the instructor is likely teaching other courses, we recommend emailing your questions to info@geo-ict.com. We’ll forward your inquiry to the instructor, and you’ll receive a response within 24 hours. After the 2-week period, we recommend using our Personalized Online Support for continued assistance.
Yes, we offer on-site training regularly throughout the Netherlands. Our instructor will bring laptops for the participants, and all you need to do is arrange a suitable room at your location.
Please send your requirements to info@geo-ict.com, and we will provide a customized quote, which will include travel and accommodation costs. Once the quote is confirmed, our course coordinator will reach out to schedule the training days.
After each course, participants receive a link to our evaluation portal where you can share your feedback on what you liked and didn’t like. We strive to provide a great experience for all our participants, but if you have a complaint, please click on ‘Complaints Procedure’ in the portal. This document will guide you through the steps to take. Geo-ICT Training Center, Netherlands, is a member of the Dutch Council for Training and Education (NRTO), ensuring a fair and transparent process.
Courses are typically scheduled according to the Dutch time zone, with sessions running from 9:00 AM to 12:00 PM and 1:00 PM to 4:00 PM. For participants in different time zones, we adjust the course times in consultation with you.