In this online data science course, you will dive into computer vision as a field of study and research. Using the classic computer vision perspective, you will explore several computer vision tasks and suggested approaches. You will also review deep learning methods and apply them to some of the same problems. Finally, you will analyze your results and discuss advantages and drawbacks of both types of methods.

By completing this course, you will be able to:

  • Explain what computer vision is and give examples of computer vision tasks
  • Describe the process behind classic algorithmic solutions to computer vision tasks and explain their pros and cons
  • Use hands-on modern machine learning tools and Python libraries

This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program.

Enroll Now