Doctor of Philosophy in Artificial Intelligence
Doctor of Philosophy in Artificial Intelligence program is designed for the Artificial Intelligence field, delivering doctoral research preparation, 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 doctoral program prepares advanced researchers through independent research, academic standards, original problem analysis, and dissertation outcomes. 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 doctoral research-methods training, topical seminars, and academic standards training.
- Develop a stable research question in the field and conduct independent, systematic research.
- Complete the doctoral dissertation and the required research outputs specified by the program.