Associate of Science in Artificial Intelligence
Associate of Science in Artificial Intelligence provides foundational associate-level preparation in Artificial Intelligence. This field covers machine learning, deep learning, large models, intelligent systems, and AI engineering applications, developing data modeling, algorithm implementation, system integration, and responsible AI capability.
Program Positioning
The associate program builds entry-level higher-education foundations, practical awareness, and learning ability for further study or junior professional work. This field covers machine learning, deep learning, large models, intelligent systems, and AI engineering applications, developing data modeling, algorithm implementation, system integration, and responsible AI capability.
Machine Learning Foundations
Study supervised learning, unsupervised learning, feature engineering, model training, and performance evaluation.
Deep Learning and Large Models
Understand neural networks, deep learning frameworks, natural language processing, computer vision, and large-model applications.
Data and Intelligent Systems
Practice data collection, cleaning, annotation, knowledge representation, intelligent application design, and system integration.
AI Engineering and Ethics
Develop skills in model deployment, testing, monitoring, privacy protection, algorithmic bias, and responsible AI practice.
Learning Objectives
Study and Completion Requirements
- Complete foundational major courses, general education courses, and introductory practical training.
- Master common concepts, basic tools, and standard forms of expression in the field.
- Meet the foundation required for bachelor's-level study or entry-level professional work.