Computer Vision with OpenCV & PyTorch
Build systems that see. Master image processing with OpenCV, train deep CNNs with PyTorch, implement object detection with YOLO, and deploy vision models to production.
What You'll Learn
Process, transform, and augment images with OpenCV and PIL
Build custom CNN architectures for image classification
Implement object detection with YOLOv8
Perform image segmentation with Mask R-CNN
Use data augmentation strategies for small datasets
Deploy a computer vision API with FastAPI and Docker
Curriculum Breakdown
Learning Format
Video Lessons
High-quality recorded lessons you can watch at your own pace.
Hands-on Projects
Real-world projects that reinforce every concept you learn.
Certificate
Earn a verifiable certificate upon successful completion.
Certification Details
Computer Vision Certificate
Issued by Tech101
Validate your computer vision expertise from image processing to production deployment.
Certificate Requirements
- Shareable on LinkedIn
- PDF download
- Unique verification ID
Completion Certificate
Awarded upon finishing all course content and submitting projects. Shows dedication and completion.
Graded Certificate
Earned by passing the final assessment with 70%+ score. Demonstrates verified skill proficiency.
Your Instructor
Sarah Johnson
Data Scientist & ML Engineer
Sarah has 10 years of experience in data science and machine learning, previously at Google AI and DeepMind.
Requirements & Prerequisites
Technical Requirements
- Deep Learning Fundamentals (PyTorch experience required)
- Basic linear algebra (matrices and vectors)
Who This Course Is For
- Deep learning practitioners specialising in visual data
- Engineers building autonomous systems, drones, or medical imaging tools
- Data Science & AI track students
Student Reviews
Frequently Asked Questions
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