AI and Computer Vision

MSDS 462-DL AI and Computer Vision.

A review of specialized deep learning methods for vision, including convolutional neural networks, vision transformers, diffusion models for generative AI, region-based convolutional neural networks, you-only-look-once models, and state-of-the-art text-to-image methods. Students work through the computer vision project lifecycle using deep learning and image processing software. They process raw image data, converting pixels into numeric tensors for analysis, object detection, classification, and segmentation. They see applications for visual exploration, tracking, multimodal AI, facial recognition, medical diagnostics, image generation, and custom solutions. Recommended prior course: MSDS 458-DL Artificial Intelligence and Deep Learning. Prerequisites: (1) MSDS 420-DL Database Systems or CIS 417 Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.

Students benefit by taking the Python Learning Studio and MSDS 430 Python for Data Science prior to taking this course.

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