SOFT 214 Introduction to Deep Learning Fundamentals

This course is designed to introduce students to the exciting field of deep learning, a subset of machine learning that has revolutionized artificial intelligence. Deep learning techniques, inspired by the structure and function of the human brain, have enabled computers to learn and make decisions from data with unprecedented accuracy. In this course, students will explore the foundations of deep learning, understand its applications in various domains, and gain hands-on experience implementing deep learning models.

Credits

5

Cross Listed Courses

N/A

Prerequisite

none

Offered

Fall, Spring

Outcomes

  1. Define deep learning and understand its significance in the broader field of artificial intelligence.
  2. Explore the historical development and key milestones in deep learning.
  3. Develop a foundational understanding of neural networks, including basic architecture and functioning.
  4. Apply the principles of model training, including loss functions and optimization algorithms.
  5. Gain hands-on experience with popular deep learning libraries such as TensorFlow and PyTorch.
  6. Understand the practical aspects of building, training, and evaluating deep learning models.
  7. Understand the role of deep learning in Natural language processing (NLP) and understanding natural language.
  8. Implement basic reinforcement learning algorithms and understand their use cases.

Area of Study:

Career Education, HS/Tech HS

Instructional Mode:

Online, Hybrid, In-person

Campus:

Central

Lecture

50