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Deep Learning for Computer Vision: CNNs and Advanced Tools
Master deep learning for computer vision. Learn CNN architectures, image classification, and object detection using TensorFlow and Python.
Course Cost
₹ 2,699
Intermediate
Skill Level
20 Hours
Self-paced lessons
Dive into the world of Computer Vision and Deep Learning with this comprehensive course. You'll explore both classic and modern approaches to Computer Vision tasks, focusing on Deep Learning applications. Learn about Convolutional Neural Networks (CNNs), image classification, object detection, and advanced deep learning tools. Gain hands-on experience with TensorFlow and Python libraries, analyzing results and comparing traditional and deep learning methods. This course is ideal for those with a background in calculus and linear algebra, looking to apply deep learning to computer vision problems.
7,264 Enrolled
English
What you'll learn
Explain Computer Vision concepts and provide examples of various Computer Vision tasks
Describe classic algorithmic solutions to Computer Vision problems and analyze their pros and cons
Use modern machine learning tools and Python libraries for Computer Vision applications
Understand the architecture and components of Convolutional Neural Networks (CNNs)
Build, train, and apply neural networks and CNNs for image classification using TensorFlow
Analyze and compare the performance of classic Computer Vision methods and Deep Learning approaches
Explore advanced Deep Learning tools and techniques for Computer Vision tasks
Apply Deep Learning methods to various Computer Vision problems such as object detection and facial recognition
Skills you'll gain
This course includes:
7.48 Hours PreRecorded video
4 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course provides a comprehensive introduction to Deep Learning applications in Computer Vision. Students will explore both classic Computer Vision techniques and modern Deep Learning approaches. The curriculum covers fundamental concepts of Computer Vision tasks, neural networks, and Convolutional Neural Networks (CNNs). Participants will gain hands-on experience using TensorFlow and Python libraries to build, train, and apply deep neural networks for image classification and other Computer Vision tasks. The course emphasizes practical skills and analysis of results, comparing traditional methods with deep learning techniques.
Introduction and Background
Module 1 · 4 Hours to complete
Classic Computer Vision Tools
Module 2 · 4 Hours to complete
Image Classification in Computer Vision
Module 3 · 2 Hours to complete
Neural Networks and Deep Learning
Module 4 · 4 Hours to complete
Convolutional Neural Networks and Deep Learning Advanced Tools
Module 5 · 6 Hours to complete
Fee Structure
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.5
19
Reviews
7,833
Students
2
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Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.