Computer Vision
offered by Carnegie Mellon University

Private University
140 acre campus
Estd. 1900

Computer Vision
at
Carnegie Mellon University
Overview

Master the core computer vision skills advancing robotics and automation

Duration	10 weeks
Total fee	₹1.46 Lakh
Mode of learning	Online
Difficulty level	Intermediate
Official Website	Go to Website
Course Level	UG Certificate

Computer Vision
at
Carnegie Mellon University
Highlights

Programming Assignments
Knowledge Checks
Dedicated Program Support Team
Discussion Boards
Bite-Sized Learning
Earn a Certification after completion

Computer Vision
at
Carnegie Mellon University
Course details

Who should do this course?

Software developers/technology professionals who want to get a deep understanding of computer vision tools and advance their career with a certificate from a renowned school.

What are the course deliverables?

Implement fundamental image processing methods and learn about various techniques used in them
Use neural networks to perform image recognition and classification
Extract 3D information from images and learn the basic principles of geometry-based vision
Align and track objects in a video

More about this course

With advances in machine learning (ML), the field of computer vision and its applications are growing by leaps and bounds, triggering transformations across industries and in daily life.
Computer Vision is an online program offered by the Executive Education division of Carnegie Mellon University’s School of Computer Science.
It enables software developers, ML engineers, and technology professionals to expand their knowledge with computer vision and image processing skills to become truly future-ready.

Computer Vision
at
Carnegie Mellon University
Curriculum

Module 1: Introduction to Computer Vision

Module 2: Image Processing

Module 3: Feature Detection and Matching

Module 4: Image Classification and Neural Networks

Module 5: Convolutional Neural Networks (CNNs)

Module 6: Transformation and Homographies

Module 7: Camera Models

Module 8: Geometry-Based Vision

Module 9: Dealing With Motion

Module 10: Physics-Based Vision

Computer Vision
at
Carnegie Mellon University
Faculty details

KRIS KITANI

Kris Kitani works in the areas of computer vision, machine learning and human-computer interaction. His research interests lie at the intersection of first-person vision, human activity modeling, and inverse reinforcement learning.

Computer Vision
at
Carnegie Mellon University
Entry Requirements

Eligibility criteria Up Arrow Icon

This program requires a functional knowledge of linear algebra, calculus, probability, and statistics. Participants should be comfortable programming in Python. Programming assignments will present opportunities to implement computer vision algorithms using these technologies.

Conditional Offer Up Arrow Icon

Yes
The Universities' Heinz College occasionally admit students to the program with condition(s) placed on their enrollment. A condition will be clearly stated within the admission offer letter.