CE-ITCS-4000 - Advanced Spatial Data Science Applications with Python

Course Description

AI and machine learning are constantly evolving fields of study, and in this hands-on course you’ll learn how to use advanced machine learning libraries utilizing geospatial data to train your own deep learning models.

Is This Course for You?

This course is designed for data science professionals currently working in geospatial analysis, data analysis, data science, or other types of computerized data with prior knowledge of commercial geospatial technology and Python programming concepts with a particular interest in remote sensing applications. This course is one of the five elective options for the Spatial Data Science Applications Mastery Certificate and is part of the GIS development (GIS-D) track, which is designed for professionals with strong computing backgrounds looking to learn more about Python applications for geospatial data, spatial analysis as a methodology, using geospatial technology, spatial analytics, and creating geographic visualizations. You can learn more about which track is best for your career trajectory and goals here [link to mastery certificate page]. If you’re pursuing the mastery certificate we strongly recommend you take this course after finishing all three core courses.

Prior experience with Python computer programming and specific computing hardware (recent NVIDIA graphics processing unit/GPU) is required for this course.

What You’ll Learn

In this course, you’ll learn the skills required for advanced machine learning libraries that utilize commercial geospatial technology for deep learning. Topics you’ll cover include training deep learning models, accuracy assessment, 2D and 3D object detection, categorization, and classification. In addition, you’ll get practical experience selecting, training, and assessing the accuracy of deep learning models applied to classification problem-solving. As a contribution to the professional portfolio you’ll work on throughout the courses in the Spatial Data Science Applications Mastery Certificate, you’ll create training models for classification problems that can run classification algorithms, as verified by the instructor and validated by accuracy assessment methods such as Confusion Matrix and F1.

How You’ll Learn

This 12-week course is fully online but does include required synchronous sessions. To learn more about the time of the required synchronous sessions, click the “+” icon next to the available course dates. Throughout this hands-on, experiential focused course, you’ll practice with deep learning models, problem-solving activities, and more.

Skills You Walk Away With

By the end of this course, you will be able to:

• Install deep learning libraries for use with ArcGIS Pro.
• Operate deep learning libraries such as TensorFlow, PyTorch, and Keras.
• Conduct feature extraction, pixel classification, and feature categorization using neural nets.
• Demonstrate how to utilize assessment methodologies to compare and contrast the accuracy of different deep learning models.

Notes

Applies Towards the Following Certificates

• Spatial Data Science Applications : GIS-Development Elective Track