Computer Vision at Carnegie Mellon University Overview
Computer Vision
at Carnegie Mellon University
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  |
Computer Vision
Table of contents
Computer Vision at Carnegie Mellon University Highlights
Computer Vision
at Carnegie Mellon University
- Programming Assignments
- Knowledge Checks
- Dedicated Program Support Team
- Discussion Boards
- Bite-Sized Learning
- Earn a Certification after completion
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Computer Vision at Carnegie Mellon University Course details
Computer Vision
at Carnegie Mellon University
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
Computer Vision
at Carnegie Mellon University
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
Computer Vision
at Carnegie Mellon University
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
Computer Vision
at Carnegie Mellon University
PTE
- No specific cutoff mentioned
Other eligibility criteria
- 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.
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Computer Vision at Carnegie Mellon University Contact Information
Computer Vision
at Carnegie Mellon University
Address
5000 Forbes Ave, Pittsburgh, PA 15213, USA
Pittsburgh ( Pennsylvania)
Phone
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