Description
From Zero to Computer Vision Engineer: Build AI That Sees
Computer vision is transforming industries—from medical imaging to retail, from security to autonomous vehicles. This course takes you beyond theory and into real-world computer vision development with hands-on projects using OpenCV, TensorFlow, YOLO, SSD, and GANs.
Projects You’ll Build
- Cats vs Dogs classifier with data augmentation and transfer learning
- London Underground sign detector using YOLO and Darkflow
- Facial emotion, age, and gender recognition system for surveillance
- Credit card number reader using OCR and image processing
- AI art generator with DeepDream and Neural Style Transfer
- Medical nuclei segmentation using U-Net for cancer detection
Skills You’ll Master
- OpenCV—image filtering, edge detection, face detection
- CNNs—LeNet, AlexNet, VGG, ResNet, Inception
- Transfer learning—fine-tune ImageNet models for custom tasks
- Object detection—YOLO, SSD, TensorFlow Object Detection API
- Image segmentation—U-Net for medical and satellite imagery
- Generative models—GANs for aging faces, creating art
- Deployment—build a Flask web app with a computer vision API on AWS
Why Learn Computer Vision in 2025?
- High demand in Nigeria’s fintech, agritech, and security sectors
- Freelance opportunities for custom vision solutions (e.g., retail analytics, defect detection)
- Foundation for robotics, AR/VR, and autonomous systems
Who Should Enroll?
- Python developers expanding into AI
- Data scientists adding vision to their toolkit
- Students building capstone projects
- Entrepreneurs automating visual inspection tasks
This Course Is Your Launchpad
You won’t just follow along—you’ll build, debug, and deploy. Each project includes starter code, datasets, and step-by-step guidance, so you focus on learning, not setup.
Teach machines to see. Enroll today and become a computer vision practitioner.
