STAT 1282 - APPLIED AI AND DEEP LEARNING WITH PYTHON

Minimum Credits: 3
Maximum Credits: 3
Long Description This course introduces the fundamentals of neural networks, including key architectures such as multilayer perceptron (MLP), convolutional neural network (CNN), and recurrent neural network (RNN), along with reinforcement learning and generative models. Through hands-on work with real-world datasets, students learn to build, train, and evaluate deep learning models while developing a strong understanding of their applications in computer vision, natural language processing, time series forecasting, and text and image generation.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: LG/SNC Elective Basis
Course Requirements: PREQ: STAT 1221 or STAT 1261 or STAT 1281 or CS 1656

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