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Computer Vision

Computer Vision All-in-One: 10 Practical Projects Completed in 12 Hours

Easy, Usable Computer Vision Projects: Step-by-step learning of practical CV projects. Boost skill with real examples.

(3.2) 5 reviews

39 learners

Level Basic

Course period Unlimited

  • nomad
Python
Python
OpenCV
OpenCV
Deep Learning(DL)
Deep Learning(DL)
Machine Learning(ML)
Machine Learning(ML)
yolo
yolo
Python
Python
OpenCV
OpenCV
Deep Learning(DL)
Deep Learning(DL)
Machine Learning(ML)
Machine Learning(ML)
yolo
yolo

What you will gain after the course

  • Image and Video Processing with OpenCV: Learn from basic image preprocessing to advanced video analysis.

  • Object Detection with the latest models: Accurately detects various objects such as apples, vehicles, and people.

  • Real-time Face Recognition and Emotion Analysis:Detects faces and analyzes emotions in real time.

  • Sports Action and Pose Analysis: Tracks and visualizes player position and movement.

  • Road Traffic Sign Recognition: Acquire the technology for detecting traffic signs and traffic lights needed for autonomous vehicles.

  • Store Congestion and Customer Behavior Analysis: Analyze customer flow and behavior data to optimize the retail environment.

  • Pose Estimation and Action Recognition: Accurately estimates hand movements and 2D/3D poses with Mediapipe.

  • Deep Learning Model Design and Training: Implement and train custom AI models using TensorFlow and PyTorch.

  • Segmentation Technology: Separate objects and remove background with UNet.

Computer Vision in Practice: From Theory to Project 👍

Learn computer vision and deep learning systematically with an 'L'-shaped learning structure that can be applied directly to practice. From basic theories to advanced techniques, you can acquire all the capabilities needed in the field through practical projects. Open the path to becoming an AI expert with 10 practical projects using Python, OpenCV, and deep learning.

💡 L-shaped learning structure: from theory to practice

This course is designed to systematically learn from the basics of computer vision to practical projects through an innovative 'L-shaped learning structure'. This structure is organized around two axes:

Vertical Axis: Basic Concepts and Practice

  • Python and OpenCV Basics : Learn step-by-step from the basics of programming to the core of image processing

  • Deep Learning and Computer Vision Theory : Understanding the core concepts of AI technology that underlies computer vision

  • Step-by-step practice : A systematic practical course that allows you to apply the theory right away.

Horizontal axis: Practical projects

  • 10 different projects : Perform projects that apply technologies used in real industrial settings.

  • Build your portfolio : Complete projects that can be used immediately for employment and practice

  • Solve real-world problems : Learn how to apply AI technologies to real-world data and environments.

Beyond simply imparting skills, this course demonstrates how to apply computer vision in real-world settings. The L-shaped learning structure integrates theory and practical experience, providing a foundation for learners to grow into AI developers. Enroll now and expand the possibilities of computer vision!

10 Real-World Projects: Experience the Core of Computer Vision!

In addition to the six projects introduced below, this course offers many more exciting and practical projects. You will be able to further enhance your computer vision skills through projects applicable to various fields such as product defect inspection, real-time facial emotion analysis, abnormal behavior detection, and disaster prevention.

Going beyond theory and solving real-world problems will greatly enhance your capabilities as an AI developer.

Sports Project

Real-time soccer object detection and tracking

Autonomous driving sign recognition project

Stop sign detection and save CSV information

Traffic Analysis Project

Vehicle Detection and Tracking Using DeepSORT

Motion Recognition Project

Landmark Analysis and Gesture Classification (Rock Paper Scissors Game)

Customer Analysis Project

Escalator Object Tracking Real-Time Analysis

Access Control Project

Person identification using facial recognition

Computer Vision: A New World of Vision Opened by AI 🤔

Computer vision technology is revolutionizing our daily lives. This field of AI is moving beyond simply viewing images to understanding and interpreting the world around us.

Computer Vision in Our Lives

Computer vision is already being used in a variety of fields:

  • Smartphone Face Recognition Unlock

  • Road situation recognition for autonomous vehicles

  • Diagnosing diseases through medical imaging

  • Detection of defects in manufacturing processes

The potential of future technologies

Changes we will experience in the future:

  • Fully autonomous car

  • Smart devices that provide information through cameras

  • AI-based early disease detection system

AI is moving beyond image processing to understanding and creating images.

Life-Changing Technology

Computer vision is a revolutionary tool that has the potential to fundamentally change our lives and work. For example, personalized exercise coaching through 3D motion analysis or AI-based professional video production tools will become possible. The future of computer vision is full of infinite possibilities. Learning and utilizing this technology will be a smart choice to prepare for the future.

Why this course? 😊

📌 A composition that even beginners can follow

  • Even if you are new to deep learning and computer vision, it's okay.

  • We explain complex concepts in a friendly, easy-to-understand manner.

  • A friendly explanation of Python grammar and OpenCV basics.

📌 Practical lectures

  • We don't just focus on theory, we practice in real time using actual data.

  • Examples: facial recognition projects, defect detection projects, motion tracking projects.

📌 Reflecting the latest technology

  • We cover cutting-edge tools and techniques such as YOLO, U-Net, and Mediapipe.

  • We will systematically introduce technologies that will be continuously updated in the future.

💡 An environment where you can practice anywhere: Learning cloud AI with Google Colab

Our computer vision course using Google Colab completely breaks down the barriers to learning.

Now you can learn cutting-edge AI technologies without complex setups or expensive equipment.


  • Zero stress on setup : All code runs in Colab, so no need to worry about installation errors.

  • Ready-to-run hands-on materials : Get results and improve your skills right away with the code provided.

  • Supports various devices : laptops, desktops, tablets, etc. All you need is an internet connection

I recommend this to these people 😎

I want to learn CV basics.

Beginner learners who are new to tools like OpenCV, YOLO, and Mediapipe, or who want to learn the fundamentals of computer vision.

I would like to try out CV skills.

Anyone who wants to know how technologies like object detection, hand gesture recognition, and face recognition are used in real-world projects.


I want to gain practical experience in CV writing.

Those who want to develop practical skills through real-world problem-solving projects such as sports analysis, autonomous driving, and factory automation.

💡 This course is optimized for:

In this course, you will learn everything about computer vision from A to Z, from basic theory to practical projects. Start learning computer vision, the core of future technology, now!

  • Computer Vision Beginner

    • For those who are new to core tools such as OpenCV and YOLO

    • For those who want to systematically learn the basic principles of image processing

    • "I want to know how computers 'understand' images"

  • Learners who want hands-on project experience

    • For those who want to implement real models such as face recognition and object detection

    • Anyone who wants to bridge the gap between theory and practical application

    • "I want to apply what I've learned to solving real-world problems."

  • Aspiring Developers Preparing for Employment

    • Job seekers who need hands-on project experience

    • Anyone who wants to add a real project to their portfolio

    • "I need a real-world project that will captivate the interviewer."

  • Professionals interested in AI applications across industries

    • Anyone who wants to apply computer vision technology to their field

    • Anyone who wants to learn about AI use cases in various industries

    • “How can it apply to our company/industry?”

  • People interested in AI and deep learning

    • Anyone who wants to understand the principles of image-based AI technology

    • Anyone who wants to learn how deep learning processes visual data

    • "I'm curious about how AI 'sees' and judges images."

  • For those looking for a systematic learning path

    • Those who feel the limitations of self-study

    • Those who want to learn from basic theory to practical application in one stop

    • "I want to systematically master everything from basics to advanced techniques."

💡 After taking the course, it is your future.

This course will help you become a computer vision expert. It introduces the core competencies and opportunities you will gain after taking the course.

  • Master the core computer vision technologies

    • Skillful use of industry standard tools such as OpenCV, YOLO, and Mediapipe

    • Understanding and implementing core technology principles from image preprocessing to object detection and pose estimation

  • Gain practical experience through real-world projects

    • Carry out various projects based on real data

      Developing advanced solutions leveraging the synergy of computer vision and deep learning

    • Learn practical optimization and application methods for the latest technologies such as YOLO and Mediapipe.

    • Improve your ability to develop solutions by applying theory to real-world problems

  • Building a strong portfolio for employment

    • Completed practical projects such as "Soccer Match Analysis", "Traffic Sign Detection", and "Safety Equipment Wear Detection"

    • Create a differentiated portfolio that catches the interviewer's eye

  • Gain practical, actionable skills that you can apply immediately

    • Ability to design and prototype computer vision-based solutions

    • Know-how applied to various industries such as sports, retail, and logistics

  • Strengthening AI and deep learning convergence capabilities

    • Developing advanced solutions leveraging the synergy of computer vision and deep learning

    • Learn practical optimization and application methods for the latest technologies such as YOLO and Mediapipe.

  • Laying the foundation for career growth

    • Ready for employment in machine learning, deep learning, and data analysis

    • Building a differentiated career based on practical project experience

Things to note before taking the class 🙌

Where can I find the study materials?

  • Section 1. ‘Lecture Preparation’ -> ‘Lecture Materials’ are provided, so please make good use of them after attending the class.

Are the lecture contents updated?

  • Of course. We will develop the content based on technological advancements and your valuable opinions.

Recommended for
these people

Who is this course right for?

  • From beginners interested in AI and deep learning to developers who want hands-on projects

  • Those who want to enhance their portfolio using computer vision technology

  • Practitioners wanting to develop deep learning models readily applicable in real-world settings

  • Those who want to start a new career with AI and Computer Vision

Need to know before starting?

  • Basic IT experience

  • Passion for learning

Hello
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Learners

494

Reviews

556

Answers

4.4

Rating

25

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Curriculum

All

56 lectures ∙ (12hr 26min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

5 reviews

3.2

5 reviews

  • sjkim7128님의 프로필 이미지
    sjkim7128

    Reviews 1

    Average Rating 5.0

    5

    30% enrolled

    Just tell me the key parts - it was a good opportunity to organize the content I had learned before.

    • harleyhwan님의 프로필 이미지
      harleyhwan

      Reviews 4

      Average Rating 4.5

      4

      98% enrolled

      • jjhgwx님의 프로필 이미지
        jjhgwx

        Reviews 644

        Average Rating 4.9

        5

        6% enrolled

        This seems like a kind and helpful lecture that builds up from the basics of Python!

        • nomad
          Instructor

          Thank you for leaving a review! 😊 I'm glad the course helped, as it's designed to build up your Python skills step by step, starting with the basics. The course is constantly evolving, and I plan to keep improving it! I plan to naturally replace the TTS throughout the lecture, and will be adding more projects, so please stay tuned for updates. I hope you continue to enjoy learning! 🚀

      • jaehyun4349님의 프로필 이미지
        jaehyun4349

        Reviews 5

        Average Rating 3.6

        Edited

        1

        28% enrolled

        Hmm.. All lectures are TTS.. It's an expensive course compared to others, but the quality of the lectures themselves is low... They just keep copy-pasting the same content to extend the lecture time, so you have to keep skipping through... It's the worst lecture. I recommend taking other courses... It's a waste of money unless it's company money...

        • flynn777님의 프로필 이미지
          flynn777

          Reviews 1

          Average Rating 1.0

          Edited

          1

          9% enrolled

          Most of the explanations are done with TTS. The consistent tone throughout the lecture makes it very off-putting. Due to the nature of TTS, it mispronounces many things, such as reading "json" as "J. S. O. N." sometimes and "Sun" at other times. I couldn't help but chuckle when the TTS voice pronounced output_labels_path as "output underscore labels underscore." The lecture content is generally poor, and there are instances where the lecture time is artificially inflated with redundant content. The project also only skims the surface of very basic aspects. This is my first time leaving a review, and I hope that those who read this review will save their money and spend it on better quality lectures or other worthwhile things.

          • nomad
            Instructor

            Thank you for leaving your valuable feedback. I'm sorry to hear that you had many unsatisfactory experiences while taking the course. I also feel that the TTS part needs improvement, so I plan to replace the entire lecture with natural voice. In addition, I plan to refine and supplement the lecture content and project part in more depth. I will carefully reflect the feedback you mentioned and develop it into a more fruitful lecture. You mentioned that this is the first time you have left a course review, Thank you again for sharing your honest opinion. I will strive to provide better lectures in the future.

        $152.90

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