Learn computer vision Online: Free Course with AI Tutor & Certificate
This 1-hour computer vision course packs 37 video lessons into a focused learning experience. You'll master fundamentals, image processing, and deep learning using Python. By the end, you can confidently build real-time object detection systems and face recognition tools using TensorFlow and Keras.
What you'll learn in this computer vision course
Five concrete outcomes you'll walk away with, each mapped to modules in the curriculum below.
Understand the fundamentals of computer vision, image processing, and their real-world applications.
Perform image transformations, filtering, edge detection, and feature extraction techniques.
Implement image segmentation, object detection, and advanced computer vision techniques using Python.
Build and fine-tune deep learning models for computer vision tasks using TensorFlow/Keras.
Apply advanced concepts like face recognition, OCR, and image generation with GANs.
computer vision course syllabus
01 Introduction to Computer Vision
- What is Computer Vision? – A Gentle Introduction
- Key Applications of Computer Vision in AI
- Image Processing VS Computer Vision
- How to Get A Job as a Computer Vision Engineer
- Computer Vision Engineer Career Path | Role, Skills, Scope, Salary, Roadmap
02 Image Processing and Computer Vision Fundamentals
- Understanding Pixels and Images as Arrays
- Image Transformations: Resizing, Cropping, Rotating
- Filters and Convolution in Images
- Blurring Techniques: Gaussian, Median, Bilateral
- Edge Detection: Sobel, Canny, and Laplacian Filters
03 Feature Detection and Matching in Computer Vision
- What Are Features in an Image?
- Corner Detection: Harris and Shi-Tomasi
- SIFT (Scale-Invariant Feature Transform) Explained
- ORB: Efficient Feature Extraction
- Feature Matching with FLANN and BFMatcher
04 Image Segmentation and Computer Vision Techniques
- What is Image Segmentation?
- Threshold-Based Segmentation
- Region-Based Segmentation
- Contour Detection and Analysis
- Watershed Algorithm for Segmentation
- K-means Clustering for Image Segmentation
05 Object Detection and Computer Vision
- Introduction to Object Detection Techniques
- Sliding Window and Image Pyramid
- HOG Feature Vector Calculation
- Introduction to Deep Learning for Detection
- YOLO (You Only Look Once) – Architecture and Demo
- SSD (Single Shot Detector)
06 Deep Learning in Computer Vision
- Introduction to CNNs (Convolutional Neural Networks)
- Building Your First CNN in TensorFlow/Keras
- Data Augmentation Techniques
- Transfer Learning in Vision (Using VGG, ResNet, etc.)
- Fine-tuning Pre-trained Models
07 Advanced Topics in Computer Vision
- Python Face Recognition
- Face Detection Using Webcam Python
- Image Captioning and Visual Question Answering
- Optical Character Recognition (OCR) with Tesseract
- Image Generation with GANs
Real-world projects you'll work on
Practice the exact kind of work computer vision professionals do on the job.
"Developing a Real-Time Object Detection System for Autonomous Vehicles"
"Creating an Advanced Image Segmentation Tool for Medical Imaging"
"Implementing a Face Recognition Security System for Corporate Access Control"
"Designing a Visual Question Answering Model for E-commerce Product Search"
Skills you'll gain
Add these to your LinkedIn profile and resume the day you finish.
Who should take this computer vision course?
And exactly what you need before starting (spoiler: almost nothing).
This course is for
- Data science students looking to specialize in visual data processing.
- Software engineers wanting to build AI-powered vision applications.
- Working professionals in India seeking to transition into machine learning roles.
- Hobbyists interested in facial recognition and self-driving car technology.
Prerequisites
- Basic understanding of Python programming is recommended.
- Familiarity with fundamental machine learning concepts will help you progress faster.
How learning works on LearnTube
The structure of a bootcamp, the price of free.
AI curates your path
Our AI picks the top 1% of video content for each topic and arranges it into a structured, goal-based curriculum. No more tutorial roulette.
Learn, then get quizzed
After every lesson, your AI tutor asks you a question and gives personalised feedback on your answer, so gaps get fixed immediately.
Finish with proof
Complete the course, build the capstone project, and claim a certificate recognised by 900+ hiring partners.
A complete computer vision course: free, structured and job-focused
In just about 1 hours across 37 video lessons, this free computer vision course teaches you how machines interpret visual data. You'll start with the Introduction to Computer Vision module and move quickly into Image Processing and Computer Vision Fundamentals. From there, the curriculum covers Feature Detection and Matching in Computer Vision and Image Segmentation and Computer Vision Techniques. You will also explore Object Detection and Computer Vision before advancing to Deep Learning in Computer Vision and Advanced Topics in Computer Vision. Every concept is grounded in practical Python applications.
The training includes four hands-on projects to build your portfolio. You'll tackle Developing a Real-Time Object Detection System for Autonomous Vehicles and Creating an Advanced Image Segmentation Tool for Medical Imaging. Later, you will build a Face Recognition Security System for Corporate Access Control and finish with Designing a Visual Question Answering Model for E-commerce Product Search. These projects ensure you know how to apply TensorFlow and Keras to real-world tasks.
LearnTube makes mastering these skills highly interactive. We curate the best YouTube tutorials and pair them with an AI tutor that tests your knowledge. After every video, you'll take a quick quiz to reinforce what you just learned. The learning is entirely free, and you can add a verified certificate at the end if you want to show employers your new technical abilities.
Jobs you can target after learning computer vision
computer vision is a gateway skill for some of the fastest-growing roles in tech.
Designs and deploys models that allow computers to interpret visual information.
Builds deep learning systems for object detection and image segmentation.
Analyzes complex image datasets to extract business insights.
Integrates visual recognition features into consumer applications.
Typical entry-level salary ranges in India as of August 2026. Actual compensation varies by city, company and experience.
Earn a computer vision certificate employers recognise
Finish the course and claim a certificate you can share anywhere.
- Learn 100% free: every lesson, quiz and the AI tutor cost nothing
- Claim your certificate when you complete the course (an optional paid add-on)
- Recognised by 900+ hiring partners across India
- One click to share on LinkedIn and add to your resume
Why learners choose LearnTube
Real reviews from Google. You learn free, you get assessed free, and you pay only if you want the certificate.
Though I have 11 years of experience as an HRBP, the course helped me refresh my knowledge and gave me insights into new trends in the market. The modules were clear and easy to understand, and the quizzes were well designed. I have added the certificate to my LinkedIn profile.
I had a lot of doubts while learning, but the AI chatbot answered them in detail with simple summaries. The videos on the platform saved me a lot of time as I didn't have to search YouTube and watch random content.
Just earned my certificate in HR Management from LearnTube.ai! The platform is user-friendly and the assessment was a great way to validate my knowledge. Feeling proud of this accomplishment!
I enrolled in a LearnTube personalized course to get into a Data Analytics role. It helped me learn SQL in depth and gave me hands-on experience with Power BI. I attached the LearnTube certificate to my CV, it added credibility to my profile, and I'm currently in the interview process.
The interface is user-friendly and intuitive, making it easy to navigate the course. I encountered no errors during my time using the platform, which was a refreshing change from other online learning platforms.
Just cleared the Business Analyst assessment and got certified! Loved how the course simplifies big concepts like data-driven decision making into short, practical lessons. The automated quizzes kept me on track the whole time. Perfect boost for my resume!
The certificate gave me a real edge during my B.Tech. By the time I graduated, I had skills that set me apart from my peers, and the certification opened up more job opportunities. It gave me the confidence to stand out during interviews.
I manage many software projects as a General Manager and was looking for a good certification program to stay competitive. After researching many programs, I chose LearnTube and it was much better than I expected. The material is well-organized and practical, and what I liked most is the lifetime access.
Frequently asked questions
Everything learners ask before starting this computer vision course.
Is this computer vision course really free?
Yes. You can watch all 37 video lessons and take the AI quizzes at no cost. The only paid feature is the optional certificate, which you can purchase after finishing the modules.
Do I need to know Python before starting?
Yes, basic Python knowledge is highly recommended. The course teaches you how to implement image segmentation and deep learning models using Python libraries like TensorFlow and Keras.
How does this compare to watching YouTube videos?
We structure the best YouTube content into a logical syllabus. Instead of guessing what to watch next, you follow a clear path and answer AI-generated quizzes after every video to test your understanding.
Will I get a computer vision certification?
You can earn a verified certificate by completing the course and passing the final assessments. This is a paid add-on that you can attach to your resume or LinkedIn profile.
Are computer vision classes worth taking right now?
Absolutely. Companies heavily rely on visual data for everything from autonomous vehicles to medical imaging. Learning these skills makes you highly competitive for machine learning and AI engineering roles.
How long does this computer vision bootcamp take?
The entire curriculum takes about 1 hours to complete. It is completely self-paced, so you can finish the seven modules and four projects on your own schedule.
What projects will I build in this training?
You will build four practical projects. These include a real-time object detection system for vehicles, a medical image segmentation tool, a face recognition security system, and a visual question answering model.
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