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Mat Leonard, Parnian Barekatain, Eddy Shyu, Brok Bucholtz, Elizabeth Otto Hamel, Cindy Lin, Cezanne Camacho, Arpan Chakraborty, Luis Serrano, and Juan Delgado

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What's inside

Syllabus

Learn what computer vision is all about, its applications in the field of artificial and emotional intelligence.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines computer vision, which is common in artificial intelligence and emotional intelligence
Provides examples in the field of artifical and emotional intelligence
Suggested for beginners who want to understand computer vision and its applications

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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 Computer Vision with these activities:
Follow a Coursera course on computer vision
Taking a Coursera course on computer vision will provide you with a structured learning experience and expose you to new concepts and techniques.
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  • Research different Coursera courses on computer vision.
  • Choose a course that fits your level of experience and interests.
  • Follow the course lectures and complete the assignments.
Solve computer vision Leetcode problems
Solving Leetcode problems will help you practice your computer vision skills and reinforce your understanding of the concepts.
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  • Find a list of computer vision Leetcode problems.
  • Start solving the problems, starting with the easier ones.
  • Review your solutions and identify areas where you can improve.
Mentor a junior computer vision student
Mentoring a junior computer vision student will help you solidify your knowledge and give back to the community.
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  • Identify a junior computer vision student who could benefit from your mentorship.
  • Meet with the student regularly and provide guidance and support.
  • Help the student develop their skills and knowledge.
Five other activities
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Attend a computer vision conference or meetup
Attending a computer vision conference or meetup will allow you to connect with other professionals in the field and learn about the latest trends.
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  • Research upcoming computer vision conferences or meetups in your area.
  • Register for the event and attend the sessions.
  • Network with other attendees and exchange ideas.
Attend a computer vision workshop
Attending a computer vision workshop will provide you with hands-on experience and exposure to new techniques.
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  • Research different computer vision workshops that are relevant to your interests.
  • Choose a workshop that fits your level of experience and goals.
  • Attend the workshop and participate in the activities.
Write a blog post on a computer vision topic
Writing a blog post on a computer vision topic will help you consolidate your knowledge and share it with others.
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  • Choose a computer vision topic that you are familiar with.
  • Research the topic and gather information from credible sources.
  • Write a draft of your blog post, including an introduction, body, and conclusion.
  • Edit and proofread your blog post.
  • Publish your blog post on a platform like Medium or LinkedIn.
Contribute to an open-source computer vision project
Contributing to an open-source computer vision project will allow you to collaborate with other developers and learn from their experiences.
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  • Find an open-source computer vision project that you are interested in.
  • Review the project's documentation and codebase.
  • Identify an area where you can contribute.
  • Make changes to the codebase and submit a pull request.
Build a computer vision project
Building a computer vision project will allow you to apply your skills to a real-world problem and gain valuable experience.
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  • Identify a problem that you want to solve with computer vision.
  • Design and develop a solution using computer vision techniques.
  • Test and evaluate your solution.
  • Deploy your solution and share it with others.

Career center

Learners who complete Computer Vision will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineers use computer vision technology to automate visual processes, such as image recognition, object detection and tracking, and image analysis. With a background in Computer Vision, you will be well-prepared for this career. This course introduces you to the concepts of computer vision so that you can leverage it in your role as a Computer Vision Engineer.
Artificial Intelligence Engineer
Artificial Intelligence Engineers research and develop artificial intelligence systems. As an Artificial Intelligence Engineer, you will use computer vision to create visual recognition systems. This course will help you build a foundation for a successful career in artificial intelligence.
Robotics Engineer
Robotics Engineers design, build, and maintain robots. Computer Vision allows robots to 'see' and process visual information, such as shapes and movements. By taking this course, you can advance your understanding of how robots can leverage computer vision.
Autonomous Vehicle Engineer
Autonomous Vehicle Engineers develop and test self-driving cars. They use computer vision to enable vehicles to perceive their surroundings. This course will prove helpful as you work to build your career as an Autonomous Vehicle Engineer.
Mechanical Engineer
Mechanical Engineers use computer vision to design and test mechanical systems, such as engines and robots. This course may be useful for you as a Mechanical Engineer, as it will help you build a foundation in computer vision.
Biomedical Engineer
Biomedical Engineers use computer vision to develop medical devices and applications. This course may be useful for you as a Biomedical Engineer, as it will help you build a foundation in computer vision.
Civil Engineer
Civil Engineers use computer vision to design and build infrastructure, such as bridges and buildings. This course may be useful for you as a Civil Engineer, as it will help you build a foundation in computer vision.
Data Scientist
Data Scientists use computer vision to analyze data and extract insights. This course may be useful for you as a Data Scientist, as it will help you build a foundation in computer vision.
Entrepreneur
Entrepreneurs use computer vision to develop and launch new products and services. This course may be useful for you as an Entrepreneur, as it will help you build a foundation in computer vision.
Electrical Engineer
Electrical Engineers use computer vision to design and test electrical systems, such as power plants and telecommunications networks. This course may be useful for you as an Electrical Engineer, as it will help you build a foundation in computer vision.
Medical Imaging Analyst
Medical Imaging Analysts use computer vision to analyze medical images, such as X-rays, CT scans, and MRIs. This course may be useful for you as a Medical Imaging Analyst, as it will help you build a foundation in computer vision.
Aerospace Engineer
Aerospace Engineers use computer vision to develop and test aircraft and spacecraft. This course may be useful for you as an Aerospace Engineer, as it will help you build a foundation in computer vision.
Business Analyst
Business Analysts use computer vision to analyze data and identify business opportunities. This course may be useful for you as a Business Analyst, as it will help you build a foundation in computer vision.
Software Engineer
Software Engineers use computer vision to develop and test software applications. This course may be useful for you as a Software Engineer, as it will help you build a foundation in computer vision.
Consultant
Consultants use computer vision to provide advice to clients on how to use technology to improve their businesses. This course may be useful for you as a Consultant, as it will help you build a foundation in computer vision.

Reading list

We've selected six 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 Computer Vision.
Classic textbook on computer vision. It provides a comprehensive overview of the field, and includes in-depth coverage of topics such as image processing, feature extraction, and object recognition.
Is an excellent introduction to computer vision algorithms and applications. It covers a wide range of topics, from image processing and feature extraction to object recognition and tracking.
Provides a comprehensive overview of deep learning for computer vision. It covers the latest techniques and algorithms, and includes hands-on examples in Python.
Provides a comprehensive overview of image understanding with deep learning. It covers a wide range of topics, from image processing and feature extraction to object recognition and tracking.
Provides a comprehensive overview of computer vision for medical image analysis. It covers a wide range of topics, from image processing and feature extraction to object recognition and tracking.
Provides a comprehensive overview of computer vision for human-computer interaction. It covers a wide range of topics, from image processing and feature extraction to object recognition and tracking.

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