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Computer Vision is the technology that teaches machines to interpret and understand images and video just like humans—but without the tea breaks. From facial recognition and self-driving cars to medical imaging and content moderation, the field is shaping industries across the globe.
This Certification in Computer Vision provides a structured and engaging exploration of key theories, tools, and techniques—from image processing in Python to object detection with YOLO (You only Look Once) and scene understanding with deep learning. The course builds knowledge step-by-step, ensuring that learners grasp not only the ‘how’ but also the ‘why’ behind Computer Vision workflows. Whether you’re sharpening your skills or diving in for the first time, this is your blueprint for learning Computer Vision in an accessible, thoroughly modern way.
This course gives you a solid footing in Computer Vision through a structured path of learning—starting with foundations, passing through deep learning, and finishing with modern implementations and future trends. You’ll explore libraries like OpenCV, TensorFlow, and PyTorch, and cover concepts such as feature extraction, segmentation, object tracking, image-to-image translation with GANs, and more. The final capstone project wraps everything into a portfolio-ready demonstration of your expertise—without any reference to you being on-site or learning by doing something messy in a lab.
- Accredited by CPD
- Instant e-certificate and hard copy dispatch by next working day
- Fully online, interactive course with audio voiceover
- Self-paced learning and laptop, tablet, smartphone-friendly
- 24/7 Learning Assistance
- Discounts on bulk purchases
Sneak Peek
Learning Outcomes
- Understand the key components of Computer Vision systems.
- Learn image processing using Python libraries and techniques.
- Explore object detection using YOLO (You only Look Once) and Faster R-CNN models.
- Grasp image classification, segmentation, and feature extraction methods.
- Implement scene understanding with RNNs, CNNs, and semantic segmentation.
- Gain insight into future trends and emerging applications in Computer Vision.
Who is this Course For
- Software developers keen to explore Computer Vision frameworks.
- AI enthusiasts looking to specialise in image-based technologies.
- Engineers working with automation and machine learning applications.
- Python programmers interested in applied artificial intelligence.
- Data analysts seeking to broaden their domain with visual data.
- Professionals transitioning from traditional to AI-driven workflows.
- Academics and students exploring machine perception in detail.
- Curious minds aiming to understand how machines interpret visuals.
Certification
Once you’ve successfully completed your course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99). All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.
Accreditation
All of our courses, including this Certification in Computer Vision, are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field.
Career Path
- Computer Vision Engineer – £52,000 average salary in the UK
- Machine Learning Engineer – £60,000 average salary in the UK
- AI Research Scientist – £65,000 average salary in the UK
- Imaging Data Analyst – £45,000 average salary in the UK
- Python Developer (Computer Vision focus) – £50,000 average salary in the UK
- Robotics Software Engineer – £58,000 average salary in the UK
Course Curriculum
The detailed curriculum outline of our Certification in Computer Vision is as follows:
- Module 1: Introduction and study plan
- Module 2: Overview of Computer Vision
- Module 3: Key Components of Computer Vision
- Module 4: Pattern Recognition
- Module 5: Technique and Algorithms
- Module 6: Challenges in Computer Vision
- Module 7: Basic of Image Processing with Python
- Module 8: Key Libraries for image processing in Python
- Module 9: Basic Image Operation
- Module 10: Continuation of Basic Image Operation
- Module 11: Continuation of Basic Image Operation
- Module 12: Image Representation and Feature Extraction
- Module 13: Continuation of image Representation and Feature Extraction
- Module 14: Corner Detection
- Module 15: HOG(Histogram of Oriented Gradients)
- Module 16: Image Segmentation
- Module 17: Types of image Segmentation
- Module 18: Technique and Implementations
- Module 19: K-Means Clustering
- Module 20: Watershed Algorithm
- Module 21: Summary
- Module 22: Object Detection
- Module 23: Key Concepts in Object Detection
- Module 24: Implementing Object Detection with Pre trained Models
- Module 25: YOLO(You only Look Once)
- Module 26: Faster R-CNN with TensorFlow
- Module 27: Summary
- Module 28: Image Classification
- Module 29: Key Components in image Classification
- Module 30: Implementing image Classification
- Module 31: Deep learning Methods
- Module 32: Image Recognition and Scene Understanding
- Module 33: Key Concepts
- Module 34: Implementations
- Module 35: Scene Understanding with Semantic Segmentation
- Module 36: Instance Segmentation with Mask R-CNN
- Module 37: Scene Classification with RNN and CNN
- Module 38: Continuation of Scene Classification with RNN and CNN
- Module 39: Object Tracking
- Module 40: Key Concepts
- Module 41: KLT Tracker with OpenCV
- Module 42: Deep SORT with YAOLOv4 for Detection
- Module 43: Image Generation and image to Image Translation
- Module 44: key concepts
- Module 45: Implementations
- Module 46: Image to Image Translation with Pix2Pix
- Module 47: Cycle gan for Unpaired Image to Image Translation
- Module 48: Continuation of Cycle gan for Unpaired Image to Image Translation
- Module 49: Advanced Topics in Computer Vision
- Module 50: Continuation of Advanced Topics in Computer Vision
- Module 51: Continuation of Advanced Topics in Computer Vision
- Module 52: Computer Vision Applications and Future Trends
- Module 53: Application
- Module 54: Future Trends
- Module 55: Continuation of Future Trends
- Module 56: Capstone Project
- Module 57: Project Title Real-world Object Detection and Classification System
- Module 58: Project Tasks
- Module 59: Continuation of project Tasks
- Module 60: Project Deliverables
- Module 61: Project Evaluation
- Module 62: Conclusion
- Module 63: Assignment
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- Original price was: £125.00.£20.00Current price is: £20.00. ex Vat
- 1 year
- Intermediate
- Course Certificate
- 6 hours, 36 minutes Gift this course
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