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Updated in [March 06th, 2023]

Learners can learn from this course:

1. Overview of running computer vision on embedded systems: Learners will gain an understanding of the fundamentals of computer vision and how to apply it to embedded systems such as Raspberry Pi and Jetson.
2. Resource constraints: Learners will learn about the resource constraints imposed by embedded systems and how to reduce resource requirements through methods such as quantization and pruning.
3. Programming assignments and projects: Learners will have the opportunity to apply their knowledge through programming assignments and projects proposed by the students.
4. Technologies: Learners will use Google Colab for programming assignments and read recently published papers.

[Applications]
After this course, students should be able to apply the concepts learned to their own projects. They should be able to use OpenCV and PyTorch on embedded systems, and be able to use quantization and pruning to reduce resource requirements. Additionally, they should be able to use Google Colab for programming assignments.

[Career Paths]
1. Embedded Systems Engineer: Embedded systems engineers are responsible for designing, developing, and testing embedded systems for a variety of applications. They must be knowledgeable in computer vision, hardware, and software development. As the demand for embedded systems increases, so does the need for embedded systems engineers.

2. Computer Vision Engineer: Computer vision engineers are responsible for developing and implementing computer vision algorithms for a variety of applications. They must be knowledgeable in computer vision, machine learning, and software development. With the increasing demand for computer vision applications, the need for computer vision engineers is also increasing.

3. Robotics Engineer: Robotics engineers are responsible for designing, developing, and testing robots for a variety of applications. They must be knowledgeable in computer vision, robotics, and software development. As the demand for robots increases, so does the need for robotics engineers.

4. Autonomous Vehicle Engineer: Autonomous vehicle engineers are responsible for designing, developing, and testing autonomous vehicles for a variety of applications. They must be knowledgeable in computer vision, machine learning, and software development. With the increasing demand for autonomous vehicles, the need for autonomous vehicle engineers is also increasing.

[Education Paths]
1. Bachelor of Science in Computer Science: A Bachelor of Science in Computer Science is a great way to gain a comprehensive understanding of computer science fundamentals and develop the skills necessary to pursue a career in the field. This degree path focuses on topics such as programming, algorithms, data structures, operating systems, computer architecture, and software engineering. With the increasing demand for computer vision applications, this degree path is becoming increasingly popular and is a great way to gain the skills necessary to develop computer vision applications for embedded systems.

2. Master of Science in Artificial Intelligence: A Master of Science in Artificial Intelligence is a great way to gain a deeper understanding of artificial intelligence and machine learning algorithms. This degree path focuses on topics such as deep learning, natural language processing, computer vision, and robotics. With the increasing demand for computer vision applications, this degree path is becoming increasingly popular and is a great way to gain the skills necessary to develop computer vision applications for embedded systems.

3. Master of Science in Computer Vision: A Master of Science in Computer Vision is a great way to gain a comprehensive understanding of computer vision algorithms and techniques. This degree path focuses on topics such as image processing, object recognition, 3D reconstruction, and motion estimation. With the increasing demand for computer vision applications, this degree path is becoming increasingly popular and is a great way to gain the skills necessary to develop computer vision applications for embedded systems.

4. Doctor of Philosophy in Computer Vision: A Doctor of Philosophy in Computer Vision is a great way to gain a comprehensive understanding of advanced computer vision algorithms and techniques. This degree path focuses on topics such as deep learning, image processing, object recognition, 3D reconstruction, and motion estimation. With the increasing demand for computer vision applications, this degree path is becoming increasingly popular and is a great way to gain the skills necessary to develop computer vision applications for embedded systems.