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Learner Reviews & Feedback for Deep Learning Applications for Computer Vision by University of Colorado Boulder

60 ratings

About the Course

In this course, you’ll be learning about Computer Vision as a field of study and research. First we’ll be exploring several Computer Vision tasks and suggested approaches, from the classic Computer Vision perspective. Then we’ll introduce Deep Learning methods and apply them to some of the same problems. We will analyze the results and discuss advantages and drawbacks of both types of methods. We'll use tutorials to let you explore hands-on some of the modern machine learning tools and software libraries. Examples of Computer Vision tasks where Deep Learning can be applied include: image classification, image classification with localization, object detection, object segmentation, facial recognition, and activity or pose estimation. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: MS in Computer Science:

Top reviews


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Great introductory course on deep learning for computer vision.


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Learnt many things and most exciting was Python code part

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1 - 12 of 12 Reviews for Deep Learning Applications for Computer Vision

By Joed H P

Jan 3, 2022

Great introductory course on deep learning for computer vision.

By Allyson D d L

Jun 17, 2022

Very good introduction but the practical exercises are so easy.

By Carlos A V S

May 19, 2022

Es un curso muy bien explicado, abarcando los conceptos básicos sobre el tema de visión por computador. Fue muy enriquecedor para mi ya que cumplió con mis expectativas. me gustó mucho la parte final que se abordó de manera práctica.

By Erik S

Mar 5, 2022

Professor Fleming is explaining verry good. Even is most of the concepts were not new to me it was a plessure how it was explained.

By Akila y

Jun 23, 2023

Great Course, The instructor explained the mathematical aspects of the course in a clear manner.

By Debasree M

Jun 17, 2022

Learnt many things and most exciting was Python code part


Mar 5, 2022

good. Thanks

By Andres F R T

Apr 7, 2023


By Triết N M

May 29, 2023

A pretty good course , The course is suitable for both beginners with no prior experience in computer vision and intermediate learners looking to enhance their knowledge and skills.

By Abhishek R

Jul 23, 2022

Great one for beginners!

By Ad m

Mar 6, 2023

not what I expect from it, but overall it's good

By Alessandro C

Nov 28, 2022

Good theoretical lessons and material suggested for further readings. However from a practical point of view the course is pretty lazy, both in showcasing the implementations of the "pytorch" library and in the requests of the assignments, which consist in remembering what was shown during lectures and copying it.