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Kimberly Karalekas
and
Vu Q Nguyen
Welcome to the Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications course!
This course provides easy access to the fundamental concepts of the Intel Distribution of OpenVINO toolkit. Throughout this course, you will be introduced to demos, showcasing the capabilities of this toolkit.
With the skills you acquire from this course, you will be able to describe the value of tools and utilities provided in the Intel Distribution of OpenVINO toolkit, such as the model downloader, model optimizer and inference engine.
Who this class is for:
This course is intended for learners with no prior...
Read more
Welcome to the Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications course!
This course provides easy access to the fundamental concepts of the Intel Distribution of OpenVINO toolkit. Throughout this course, you will be introduced to demos, showcasing the capabilities of this toolkit.
With the skills you acquire from this course, you will be able to describe the value of tools and utilities provided in the Intel Distribution of OpenVINO toolkit, such as the model downloader, model optimizer and inference engine.
Who this class is for:
This course is intended for learners with no prior...
Read more
Welcome to the Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications course!
This course provides easy access to the fundamental concepts of the Intel Distribution of OpenVINO toolkit. Throughout this course, you will be introduced to demos, showcasing the capabilities of this toolkit.
With the skills you acquire from this course, you will be able to describe the value of tools and utilities provided in the Intel Distribution of OpenVINO toolkit, such as the model downloader, model optimizer and inference engine.
Who this class is for:
This course is intended for learners with no prior experience with computer vision, although previous knowledge is helpful. This course is ideal for anyone interested in learning more about core concepts of computer vision applications and the Intel Distribution of OpenVINO toolkit.
Estimated Workload:
You should expect to allocate about 3 hours to complete this course.
Learner pre-requisites:
No prior knowledge of computer vision is necessary, although previous experience is helpful.
Register for this course and see more details by visiting:
OpenCourser.com/course/dd5y87/introduction
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores practical applications of computer vision using the Intel Distribution of OpenVINO toolkit, which is industry standard
Computer vision and the Intel Distribution of OpenVINO toolkit are valuable skills for many roles and industries
Provides easy access to fundamental concepts for learners new to computer vision
Teaches skills in using tools like the model downloader, model optimizer, and inference engine
Taught by Kimberly Karalekas and Vu Q Nguyen, recognized for their expertise in computer vision
Assumes no prior experience in computer vision
Save this course
Save Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications to your list so you can find it easily later:
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Reviews summary
Computer vision foundations with openvino
This course provides a comprehensive introduction to Intel's OpenVINO Toolkit, a powerful set of tools for developing and deploying computer vision applications. With a focus on core concepts and practical applications, this course is ideal for beginners looking to gain a solid foundation in computer vision.
Course covers a wide range of topics, providing a well-rounded understanding of computer vision.
"This course provided a beautiful and concise introduction to developing Computer Vision applications with Intel Distribution of OpenVINO Toolkit."
"I have enjoyed a lot during the classes"
"Great Overview of OpenVINO toolkit that helps in optimization and deployment of a pre-trained model independent of the device thereby abstracting the hardware aspects."
"Really a helpful course for beginner who wents to learn computer vision application development."
Instructors are knowledgeable and effectively convey the material.
"Instructor is awesome and he elaborate topic very clearly."
"Really helpful course for beginner who wents to learn computer vision application development."
"The Instructor is awesome and he elaborate topic very clearly."
"I recommend everyone take this course If you went to learn the computer vision basics"
Course is well-suited for beginners with little to no prior experience in computer vision.
"This being my first introduction to Computer Vision Toolkits I found the concise nature of the videos and structure of quizzes reinforced the absorption of the curriculum."
"The information is pretty up-to-date and for hobby learners like me who don't have much programming background, it really offers a general introduction on the topic of computer vision."
"After the course one would atleast know what is meant by computer vision and how in general it works."
"Nice Introductory course. It's motivates me to look forward the camera and automation system"
Course effectively showcases the real-world applications of OpenVINO in various industries.
"Intel ® open vino™ toolkit for computer vision application is good study material and also iam improve my computer skills . "
"Get an Overall Idea about OpenVINO Tool kit and Idea about the wide range of areas where we can use it or made our own applications"
"Provides a brief look of how things work in OpenVINO and how one can make use of it."
"Intel OpenVINO can be a great tool for developing Computer Visions applications for sure and it holds a lot of powerful features."
Top-notch course material that provides a clear and concise foundation in computer vision principles.
"Very happy to complete this course, learned a lot new things"
"It was nice organized and easy to capture key points"
"Very informative and useful course to know about OpenVINO toolkit"
"This course introduced me many applications of machine learning concepts with ease implementation of OpenVIVO toolkit."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications with these
activities:
Review Course Content Thoroughly
Show steps
Lay a solid foundation for your learning by reviewing all the course content, including video lectures, readings, and assignments.
Show steps
-
Gather all course materials
-
Allocate dedicated time for reviewing the materials
-
Take notes and highlight key concepts
Attend Industry Webinars
Show steps
Stay updated on industry trends and best practices by attending webinars hosted by experts in computer vision and the Intel Distribution of OpenVINO toolkit.
Show steps
-
Identify relevant webinars and register for them
-
Attend the webinars and actively participate in Q&A sessions
-
Take notes and follow up on any resources or contacts shared
Review Basics of Computer Vision
Show steps
Refine your understanding of the fundamental concepts of computer vision, such as image processing, feature extraction, and object detection, before beginning this course.
Browse courses on
Computer Vision
Show steps
-
Identify reliable online tutorials
-
Follow the tutorials to gain a strong foundation in computer vision
-
Practice implementing the concepts through hands-on exercises
Four other activities
Expand to see all activities and additional details
Show all seven activities
Form a Study Group
Show steps
Enhance your learning experience by joining a study group with fellow learners taking this course. Collaborate, discuss concepts, and quiz each other to strengthen your understanding.
Show steps
-
Identify potential study partners
-
Schedule regular study sessions
-
Discuss course material, share insights, and challenge each other's perspectives
Complete Coding Exercises
Show steps
Solidify your understanding of the Intel Distribution of OpenVINO toolkit by completing coding exercises. Implement the concepts covered in the course and troubleshoot any challenges encountered.
Show steps
-
Identify coding exercises from online resources or the course material
-
Set aside dedicated time for coding practice
-
Implement the coding solutions
-
Test the code and debug any errors
Participate in a Computer Vision Hackathon
Show steps
Test your skills and gain practical experience by participating in a computer vision hackathon. Collaborate with others to solve complex problems and showcase your abilities.
Browse courses on
Computer Vision
Show steps
-
Find a relevant hackathon and register
-
Form a team or collaborate with other participants
-
Develop a project idea and implement it using the Intel Distribution of OpenVINO toolkit
-
Present your project to a panel of judges
Create a Visual Tutorial
Show steps
Deepen your knowledge and share your understanding by creating a visual tutorial that demonstrates a specific concept or application of the Intel Distribution of OpenVINO toolkit for computer vision.
Show steps
-
Select a topic or application to focus on
-
Develop a storyboard and script for the tutorial
-
Create the visual content using tools like screen capture, animation, or graphics
-
Record a voiceover or write captions to explain the concepts
-
Edit and finalize the tutorial
Review Course Content Thoroughly
Show steps
Lay a solid foundation for your learning by reviewing all the course content, including video lectures, readings, and assignments.
Show steps
Show steps
Show steps
- Gather all course materials
- Allocate dedicated time for reviewing the materials
- Take notes and highlight key concepts
Attend Industry Webinars
Show steps
Stay updated on industry trends and best practices by attending webinars hosted by experts in computer vision and the Intel Distribution of OpenVINO toolkit.
Show steps
Show steps
Show steps
- Identify relevant webinars and register for them
- Attend the webinars and actively participate in Q&A sessions
- Take notes and follow up on any resources or contacts shared
Review Basics of Computer Vision
Show steps
Refine your understanding of the fundamental concepts of computer vision, such as image processing, feature extraction, and object detection, before beginning this course.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Identify reliable online tutorials
- Follow the tutorials to gain a strong foundation in computer vision
- Practice implementing the concepts through hands-on exercises
Four other activities
Expand to see all activities and additional details
Show all seven activities
Form a Study Group
Show steps
Enhance your learning experience by joining a study group with fellow learners taking this course. Collaborate, discuss concepts, and quiz each other to strengthen your understanding.
Show steps
Show steps
Show steps
- Identify potential study partners
- Schedule regular study sessions
- Discuss course material, share insights, and challenge each other's perspectives
Complete Coding Exercises
Show steps
Solidify your understanding of the Intel Distribution of OpenVINO toolkit by completing coding exercises. Implement the concepts covered in the course and troubleshoot any challenges encountered.
Show steps
Show steps
Show steps
- Identify coding exercises from online resources or the course material
- Set aside dedicated time for coding practice
- Implement the coding solutions
- Test the code and debug any errors
Participate in a Computer Vision Hackathon
Show steps
Test your skills and gain practical experience by participating in a computer vision hackathon. Collaborate with others to solve complex problems and showcase your abilities.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Find a relevant hackathon and register
- Form a team or collaborate with other participants
- Develop a project idea and implement it using the Intel Distribution of OpenVINO toolkit
- Present your project to a panel of judges
Create a Visual Tutorial
Show steps
Deepen your knowledge and share your understanding by creating a visual tutorial that demonstrates a specific concept or application of the Intel Distribution of OpenVINO toolkit for computer vision.
Show steps
Show steps
Show steps
- Select a topic or application to focus on
- Develop a storyboard and script for the tutorial
- Create the visual content using tools like screen capture, animation, or graphics
- Record a voiceover or write captions to explain the concepts
- Edit and finalize the tutorial
Career center
Learners who complete Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers use their understanding of deep learning, computer vision, and artificial intelligence to build systems that can recognize and interpret images and videos. This course provides a deep dive into Intel's OpenVINO toolkit, a popular framework for developing computer vision applications, preparing you for success in this role. By learning about model optimization, inference, and other core concepts, you'll gain the skills needed to design and implement effective computer vision solutions.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers apply their knowledge of machine learning algorithms and techniques to develop and deploy machine learning models. This course offers a solid foundation in the Intel Distribution of OpenVINO toolkit, widely used in machine learning for computer vision applications. Through hands-on demos and practical examples, you'll learn how to leverage OpenVINO's capabilities, empowering you to excel as a Machine Learning Engineer in the field of computer vision.
Data Scientist
Data Scientist
Data Scientists utilize their expertise in data analysis, statistics, and machine learning to extract insights and make predictions from data. This course introduces you to the Intel Distribution of OpenVINO toolkit, an essential tool for computer vision applications in data science. By gaining proficiency in OpenVINO's model optimization and inference capabilities, you'll be well-equipped to develop and deploy data-driven computer vision solutions, enhancing your value as a Data Scientist.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course covers the fundamentals of the Intel Distribution of OpenVINO toolkit, empowering you to build robust and efficient computer vision applications. With a focus on model optimization and inference, you'll gain the necessary skills to excel as a Software Engineer specializing in computer vision.
Computer Vision Researcher
Computer Vision Researcher
Computer Vision Researchers advance the field of computer vision through theoretical and applied research. This course provides a solid foundation in the Intel Distribution of OpenVINO toolkit, widely used for computer vision research. By understanding OpenVINO's capabilities and leveraging its tools and utilities, you'll be well-equipped to conduct cutting-edge research and contribute to the development of innovative computer vision solutions.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, and maintain robots. This course offers a practical introduction to the Intel Distribution of OpenVINO toolkit, a powerful tool for computer vision applications in robotics. You'll learn how to utilize OpenVINO for object detection, image segmentation, and other computer vision tasks crucial for robot navigation and perception.
Data Analyst
Data Analyst
Data Analysts transform raw data into meaningful insights. This course may be useful for Data Analysts interested in leveraging computer vision techniques to enhance their data analysis capabilities. By understanding the basics of the Intel Distribution of OpenVINO toolkit, you'll be able to explore new possibilities for data visualization and analysis, adding value to your role as a Data Analyst.
Product Manager
Product Manager
Product Managers define and oversee the development of products. This course may be useful for Product Managers working on computer vision-related products. By gaining an understanding of the Intel Distribution of OpenVINO toolkit, you'll be better equipped to make informed decisions about product features and roadmap, ensuring the success of your computer vision products.
Business Analyst
Business Analyst
Business Analysts analyze business needs and develop solutions. This course may be useful for Business Analysts working on projects involving computer vision technology. By understanding the capabilities of the Intel Distribution of OpenVINO toolkit, you'll be able to better assess the feasibility and potential impact of computer vision solutions, adding value to your role as a Business Analyst.
UX Designer
UX Designer
UX Designers create user interfaces and experiences. This course may be useful for UX Designers working on computer vision-related products. By understanding the principles of computer vision and the capabilities of the Intel Distribution of OpenVINO toolkit, you'll be able to design user interfaces that seamlessly integrate computer vision functionality, enhancing the user experience.
IT Architect
IT Architect
IT Architects design and manage IT systems. This course may be useful for IT Architects responsible for implementing computer vision solutions. By gaining an understanding of the Intel Distribution of OpenVINO toolkit, you'll be better equipped to evaluate and select the appropriate technologies for your IT architecture, ensuring the scalability and performance of your computer vision systems.
Technical Writer
Technical Writer
Technical Writers create documentation and training materials for technical products. This course may be useful for Technical Writers specializing in computer vision or related technologies. By understanding the fundamentals of the Intel Distribution of OpenVINO toolkit, you'll be able to produce clear and concise documentation that effectively communicates the capabilities and benefits of computer vision solutions.
Project Manager
Project Manager
Project Managers plan and execute projects. This course may be useful for Project Managers working on computer vision projects. By gaining an understanding of the Intel Distribution of OpenVINO toolkit, you'll be better equipped to manage project timelines, resources, and risks, ensuring the successful delivery of your computer vision solutions.
Sales Engineer
Sales Engineer
Sales Engineers provide technical expertise to support sales efforts. This course may be useful for Sales Engineers specializing in computer vision or related technologies. By understanding the capabilities of the Intel Distribution of OpenVINO toolkit, you'll be able to effectively communicate the value and benefits of computer vision solutions to potential customers, increasing your sales success.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns. This course may be useful for Marketing Managers responsible for promoting computer vision products or services. By understanding the basics of computer vision and the capabilities of the Intel Distribution of OpenVINO toolkit, you'll be able to create targeted marketing campaigns that effectively reach your target audience.
For more career information including salaries, visit:
OpenCourser.com/course/dd5y87/introduction
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications.
Save
Provides a comprehensive overview of computer vision algorithms and techniques, covering topics such as image formation, feature detection, object recognition, and video analysis. It is an excellent resource for beginners and experienced practitioners alike.
Provides a comprehensive overview of machine learning for computer vision applications. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning. It is an excellent resource for those who want to learn how to apply machine learning to computer vision problems.
Save
Provides a comprehensive overview of pattern recognition and machine learning algorithms. It is an excellent resource for those who want to learn the theoretical foundations of these topics.
Provides a comprehensive overview of computer vision algorithms and techniques. It is an excellent resource for beginners and experienced practitioners alike.
Save
Provides a comprehensive overview of deep learning algorithms and techniques. It is an excellent resource for those who want to learn the theoretical foundations of deep learning.
Provides a comprehensive overview of computer vision algorithms and techniques. It is an excellent resource for beginners and experienced practitioners alike.
Provides a practical guide to deep learning using the Python programming language. It is an excellent resource for those who want to learn how to apply deep learning to real-world problems.
Save
Provides a comprehensive overview of pattern recognition algorithms and techniques. It is an excellent resource for those who want to learn the theoretical foundations of these topics.
Provides a comprehensive overview of machine learning algorithms and techniques from a probabilistic perspective. It is an excellent resource for those who want to learn the theoretical foundations of machine learning.
Provides a practical guide to deep learning using the fastai and PyTorch libraries. It is an excellent resource for those who want to learn how to apply deep learning to real-world problems.
Provides a comprehensive overview of machine learning for computer vision applications. It is an excellent resource for those who want to learn how to apply machine learning to computer vision problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/dd5y87/introduction
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Time
8 hours
Via
Coursera
Institution
Intel
Instructors
Kimberly Karalekas
Vu Q Nguyen
Good to know
Explores practical applications of computer vision using the Intel Distribution of OpenVINO toolkit, which is industry standard
Computer vision and the Intel Distribution of OpenVINO toolkit are valuable skills for many roles and industries
Provides easy access to fundamental concepts for learners new to computer vision
Teaches skills in using tools like the model downloader, model optimizer, and inference engine
Taught by Kimberly Karalekas and Vu Q Nguyen, recognized for their expertise in computer vision
Assumes no prior experience in computer vision
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