(IT 310) Data Engineering and Machine Learning
This course introduces learners to the fundamentals of data engineering and machine learning, enabling them to develop essential skills for analyzing large datasets and building effective machine learning models. Through hands-on experience and group projects, students will gain an understanding of the ethical considerations and best practices associated with these domains.
| Credit hours | 3.0 lecture |
|---|---|
| Prerequisites | CS 101, IT 124 |
| Offered | Variable |
| Programs | Information Technology (BS) |
Course Learning Outcomes
Each student who passes this course will be able to do the following:
- Understand and apply core concepts in data engineering and machine learning, including data preprocessing, feature extraction, model selection, and evaluation.
- Design, implement, and evaluate solutions to meet specific requirements using various machine learning algorithms and techniques.
- Effectively communicate technical concepts and project outcomes in both written and verbal formats, demonstrating collaboration skills through group project work.
- Recognize and address ethical considerations in data analytics and machine learning, including data privacy, bias, and fairness.
- Employ systematic approaches to select, integrate, and manage data analytics and machine learning tools, libraries, and frameworks.