Ementorhub

What you'll learn

Learners will be able to explain what Computer Vision is and give examples of Computer Vision tasks.

Learners will be able to describe the process behind classic algorithmic solutions to Computer Vision tasks and explain their pros and cons.

Learners will be able to use hands-on modern machine learning tools and python libraries.

Skills you'll gain

Artificial Neural Networks

Computer Vision

Computer Programming Tools

Tensorflow

Artificial Intelligence

Deep Learning

Algorithms

PyTorch (Machine Learning Library)

Image Analysis

Machine Learning

Machine Learning Algorithms

Applied Machine Learning

There are 5 modules in this course

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: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Classic Computer Vision Tools

Image Classification in Computer Vision

Neural Networks and Deep Learning

Convolutional Neural Networks and Deep Learning Advanced Tools