Quantum will start the “ML for Remote Sensing Data” course
Quantum starts the “ML for Remote Sensing Data” course for Lviv Data Science Summer from the Ukrainian Catholic University.
Course Description
This course provides an overview of remote sensing data analysis. Remote sensing data is already being used to address development issues, i.e., revealing changes in soil quality or water availability, informing agricultural interventions, and measuring poverty. In this course, we will cover basic principles of satellite imagery most popular techniques to work with it. Also, we will cover the application ranges of machine learning and computer vision on remote sensing data. As well as to get familiar with the theory of remote sensing, we will get hands-on experience in building computer vision models on satellite imagery.
Course tools
— Python, Tensorflow, Keras, Numpy, QGIS.
Prerequisites
— Python
— Machine Learning basics, including deep learning frameworks (like Keras, PyTorch)
Level of complexity of course
Intermediate
Lecturer
Michael Yushchuk is the Data Science Team Lead at Quantum with experience in many areas of Machine Learning and in-depth expertise in Computer Vision and NLP. The main domains are Agrotech, Healthcare, and Sales. Also, Michael has six years of experience in research, including four years in Computer Vision. He has several scientific publications and patents. While working at Quantum, he cooperated with Ukraine’s environmental organization. The team led by Michael automates tasks such as monitoring deforestation and the state of forest fields, detecting soil erosion, and so on.
Follow the link for course details.
We are excited to be able to invest in the future of technical education and technological progress by building a knowledge base among young professionals.
With this in mind, we will continue improving our programs and finding new ways to learn and spread ideas among young people.