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AI for Computer Vision

Build production computer vision systems with modern foundation models. CLIP, SAM, object detection, video analysis, and real-world vision pipelines.

14 hours11 modules1 projects
$22/mo
$49/mo

or $230 lifetime $799

  • Access to all 12 courses
  • All future updates
  • Certificate of completion
  • 30-day money-back guarantee

About This Course

Computer vision has been transformed by foundation models like CLIP, SAM, and GPT-4 Vision. This course teaches you to build vision systems using these modern tools — moving beyond training CNNs from scratch to leveraging powerful pre-trained models for object detection, image classification, segmentation, OCR, and video analysis in production applications.

What You'll Learn

  • Use CLIP for zero-shot image classification and visual search
  • Apply SAM (Segment Anything) for object segmentation without training
  • Build object detection pipelines with YOLO v8/v10
  • Extract structured data from documents and images with vision models
  • Design multi-modal AI systems combining vision and language
  • Process video streams for real-time analysis and event detection
  • Fine-tune vision models for domain-specific classification tasks
  • Deploy vision inference systems with optimized throughput

Who Is This For?

Python Developers

Want to add visual intelligence to their applications without deep ML expertise

AI Engineers

Expanding from NLP/text AI to multi-modal and vision capabilities

Domain Specialists

Building vision tools in healthcare imaging, manufacturing QA, retail, or security

Prerequisites

  • Python for AI
  • Understanding LLMs recommended
  • Basic familiarity with NumPy helpful

Tools & Technologies

PythonOpenCVPyTorchCLIPSAMUltralytics YOLOOpenAI Vision