SOFT 215 — Introduction to Neural Networks
This course provides an in-depth introduction to the fundamental principles, architectures, and applications of neural networks. Students will explore the theoretical foundations of neural networks, understand their mathematical underpinnings, and gain practical hands-on experience in designing and implementing neural network models. The course covers a range of topics, from basic concepts to advanced architectures such as deep neural networks and convolutional neural networks. Real-world applications, including image recognition, natural language processing, and pattern recognition, will be examined to illustrate the practical utility of neural networks. Through a combination of lectures, practical exercises, and projects, students will develop the skills needed to apply neural networks to solve complex problems.