CSCI 280 - Artificial Intelligence and Machine Learning Foundations

5 Credits

This course introduces the foundations of machine learning (ML) and artificial intelligence (AI). Students collect, evaluate, and clean data, use machine learning tools to train and deploy a model. Students will also evaluate the accuracy of the model and perform model tuning by interpreting model results for forecasting. Algorithms, computer vision, natural language processing and generative AI will be introduced. Students will have hands-on labs with standard algorithms and tools.

Pre-requisite(s) (MATH& 146 min 1.0 or CSCI 180 min 2.0) and (CSCI 132 min 2.0)
Fees

Quarters Typically Offered
Summer
Fall
Winter
Spring

Designed to Serve Students wanting to gain knowledge of data science relevant to the program of study, including students in data-adjacent fields.
Active Date 20250521T15:17:39

Grading Basis Decimal Grade
Class Limit 24
Contact Hours: Lecture 55
Total Contact Hours 55
Degree Distributions:
AA

ProfTech Course Yes
Restricted Elective Yes
ProfTech Related Instruction

BAS

Course Outline

Introduction to machine learning and artificial intelligence
1. Review of statistical methods and data types
Introduce algorithms
Knowledge representation and reasoning
Deep learning pipelines
1. Understanding bias in training
Applications of artificial intelligence
1. Natural language processing
2. Transformers and attention
3. Generative AI
4. Computer vision

Student Learning Outcomes
Understand foundational artificial intelligence concepts.

Apply statistical methods and machine learning techniques to data sets programmatically.

Evaluate model performance.

Design and implement artificial intelligence and machine learning solutions for decision making.

Interpret model results and make predictions.

Communicate insights derived through artificial intelligence.