Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications
- 4.6
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Approx. 3 hours to complete
Course Summary
The Intel OpenVINO toolkit enables developers to build and deploy deep learning inference applications at the edge by optimizing neural network models and deploying them to various Intel hardware platforms.Key Learning Points
- Learn how to optimize and deploy deep learning models at the edge
- Understand the importance of model accuracy and latency in real-world applications
- Gain hands-on experience with the Intel OpenVINO toolkit
Related Topics for further study
Learning Outcomes
- Optimize and deploy deep learning models using Intel OpenVINO
- Understand the importance of model accuracy and latency in real-world applications
- Gain hands-on experience with Intel hardware platforms
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of deep learning and computer vision
- Familiarity with Python programming
Course Difficulty Level
IntermediateCourse Format
- Online self-paced
- Hands-on projects
Similar Courses
- TensorFlow: Data and Deployment Specialization
- Deep Learning Specialization
Related Education Paths
Notable People in This Field
- Deep Learning Engineer, Intel
- AI/ML Technical Lead, Intel
Related Books
Description
Welcome to the Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications course!
Knowledge
- Foundational knowledge of Intel® Distribution of OpenVINO™ toolkit
- Foundational knowledge of deep learning for computer vision applications
- The phases of the inference flow
- Intel® hardware acceleration and optimization techniques
Outline
- Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications
- Intel® Distribution of OpenVINO™ Toolkit: Part 1
- What's included in the Intel® Distribution of OpenVINO™ Toolkit?
- Inference Flow
- Model Optimizer Concept
- Model Downloader
- Inference Engine Concept
- Intel® Distribution of OpenVINO™ Toolkit and Development Kits
- First Two Demos
- Intel® Distribution of OpenVINO™ Toolkit: Part 2
- Welcome
- Discussion Prompt Overview
- Hands-On Project
- Conclusion
- Intel® Distribution of OpenVINO™ Toolkit: Part 1
- What's included in the Intel® Distribution of OpenVINO™ Toolkit?
- Inference Flow
- Model Optimizer Concept
- Model Downloader
- Inference Engine Concept
- Intel® Distribution of OpenVINO™ Toolkit and Development Kits
- First Two Demos
- Intel® Distribution of OpenVINO™ Toolkit: Part 2
Summary of User Reviews
The Intel OpenVINO course on Coursera received positive reviews from many users. The course provides a comprehensive introduction to OpenVINO and its applications.Key Aspect Users Liked About This Course
The in-depth coverage of the OpenVINO toolkit and its practical applications was highly appreciated by many users.Pros from User Reviews
- The course provides hands-on experience with OpenVINO and real-world case studies.
- The instructors are knowledgeable and provide clear explanations.
- The course is well-structured and easy to follow.
- The course materials are of high quality and provide a good understanding of the topic.
- The course is suitable for both beginners and experienced users.
Cons from User Reviews
- Some users found the course content to be too basic.
- The course could benefit from more advanced topics and deeper coverage.
- The course could be more engaging and interactive.
- The course materials could be updated more frequently.
- The course is not suitable for those who are not familiar with programming.
Vu Q Nguyen
4.6 Raiting
Intel® Edge AI for IoT Developers
- 0.0
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15 billion by 2023, at an Annual Growth Rate of 27%. ( MarketsandMarkets ) In the Edge AI for IoT Developers Nanodegree program,...
Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications
- 4.6
-
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Welcome to the Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications course! Throughout this course, you will be introduced to demos, showcasing the capabilities of this toolkit....
