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Dec 15, 2025
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CSC 2663 - Machine Learning Techniques1 lecture hours 0 lab hours 1 credits
Course Description
This course serves as an introduction to machine learning tools commonly used to analyze data. The course covers using libraries to facilitate data analysis and machine learning tasks in Python. Students will explore deep learning and machine learning terminology and examples. This course is not available to students with credit for CSC 4601 . (prereq: CSC 2661 or program director consent) (quarter system prereq: CS 4961 or program director consent)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Describe the basic functionality and capability of NumPy and other machine learning tools such as PyTorch and TensorFlow
- Make small changes to change behavior of existing machine learning code
- Experiment with example data to explore the capabilities of deep learning and neural networks
- Describe industry examples machine learning can be used to solve real world problems
Prerequisites by Topic
- Programming experience with Python
Course Topics
- Machine learning basics
- Example machine learning code in Jupyter Notebooks
- Python libraries useful for machine learning such as, NumPy, PyTorch, and Tensor Flow
- Capabilities and limitations of deep learning and neural networks
- Case studies in machine learning
Coordinator
Dr. Jonathon Magaña
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