“智能科技+N”项目由博雅智能学院（SAI）与理工科技学院（FST）联合管理，旨在培养具有国际视野、扎实人工智能基础与跨学科创新能力的复合型本科人才。项目以人工智能为核心，通过项目制实践教学，深化学生对人工智能技术的掌握，拓展其在不同学科与行业中的创新应用能力。依托跨学科课程体系与多元实践平台，项目着力培养学生的创新思维、实践能力与国际竞争力，为其未来深造、科研及多元化职业发展奠定坚实基础。
“智能科技+N”项目由博雅智能学院（SAI）与理工科技学院（FST）联合管理，旨在培养具有国际视野、扎实人工智能基础与跨学科创新能力的复合型本科人才。项目以人工智能为核心，通过项目制实践教学，深化学生对人工智能技术的掌握，拓展其在不同学科与行业中的创新应用能力。依托跨学科课程体系与多元实践平台，项目着力培养学生的创新思维、实践能力与国际竞争力，为其未来深造、科研及多元化职业发展奠定坚实基础。
学生需根据所属专业培养方案，完成以下课程结构规定的148-152个学分：
Course Category |
Units |
|||||||||
| AI | AM | APSY | CST | DS | ENVS | FM | FS | STAT | ||
Common Core Courses (公共核心课) |
Common Core Required Courses (公共核心必修课) |
15 |
15 |
15 |
15 |
15 |
15 |
15 |
15 |
15 |
Common Core Elective Courses (公共核心选修课) |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
|
Major Required Courses (专业必修课) |
42 |
45 |
51 |
48 |
45 |
49 |
57 |
55 |
48 |
|
Major Elective Courses (专业选修课) |
18 |
12 |
12 |
18 |
12 |
12 |
9 |
18 |
15 |
|
University Core Courses (大学核心课) |
37 |
37 |
37 |
37 |
37 |
37 |
37 |
37 |
37 |
|
General Education Courses (通识教育课) |
18 |
18 |
18 |
18 |
18 |
18 |
18 |
18 |
18 |
|
Free Elective Courses (自由选修课) |
18 |
21 |
15 |
12 |
21 |
21 |
15 |
9 |
18 |
|
Total |
148 |
148 |
148 |
148 |
148 |
152 |
151 |
152 |
151 |
|
SAI公共核心课程的学分由公共核心必修课与公共核心选修课构成，以满足总学分要求。
Course Code |
Course Title |
Units |
Source |
Common Core Courses (Required) |
|||
MATH1123 |
Calculus for Science and Engineering |
3 |
MR for AI, AM, CST, DS, ENVS, FM, FS & STAT; ME for APSY |
AI1003 |
Python Programming |
3 |
MR for AI; MR for CST (equivalent to COMP2073); MR for DS (equivalent to DS2043); ME for ENVS (equivalent to DS1013); FE for AM, APSY, FS, FM & STAT |
AI2033 |
Probability and Statistics |
3 |
MR for AI; MR for AM & FM (equivalent to STAT2063); MR for DS (equivalent to DS2053); MR for ENVS & FS (equivalent to STAT1013); MR for STAT (equivalent to STAT1033) FE for APSY & CST |
AI2013 |
Introduction to Artificial Intelligence |
3 |
MR for AI; FE for AM, APSY, CST, DS, ENVS, FM, FS & STAT |
AI4005/AM4005 /PSY4005/CST4 005/DS4005/ ENV4005/FM40 05/FOOD4005/S TAT4005 |
Final Year Project II (AI)/(AM)/(PSY)/(COMP)/(DS)/(E NV)/(FM)/(FOOD)/(STAT) |
3 |
ME for AI, AM, APSY, CST, DS, ENVS, FM & STAT; FE for FS |
Total |
15 |
||
Common Core Courses (Elective) |
|||
AI2073 |
Perception |
3 |
Only for AI, CST and DS, categorized as FE. |
PSY2043 |
Introduction to Psychology |
3 |
Only for AI, AM, CSTand FM, categorized as FE. |
PSY4103 |
Cognitive Neuroscience |
3 |
Only for AI and CST, categorized as FE. |
BIOL2003 |
General Biology |
3 |
Only for AI, categorized as FE. |
CHEM2003 |
General Chemistry |
3 |
Only for AI, categorized as FE. |
ENV1043 |
Introduction to Environmental Science |
3 |
Only for AI, categorized as FE. |
ENV3073 |
Introduction to Geographic Information Systems for Environmental Management |
3 |
Only for AI, CST and DS, categorized as FE. |
ENV3193 |
Carbon Technology and Renewable Energy |
3 |
Only for AI and CST, categorized as FE. |
FOOD1033 |
Introduction to Food Science |
3 |
Only for AI and CST, categorized as FE. |
AI1012 |
Database Management Systems |
3 |
Only for APSY, ENVS, and FS, categorized as FE |
AI1013 |
Object-Oriented Programming |
3 |
Only for APSY, ENVS, and FS, categorized as FE |
AI2003 |
Data Structures and Algorithm Analysis |
3 |
Only for AM, APSY, ENVS, FM and STAT, categorized as FE |
AI2023 |
Artificial Intelligence Workshop |
3 |
Only for AM, APSY, ENVS, FM, FS and STAT, categorized as FE |
AI2053 |
Introduction to Cognitive Science |
3 |
Only for APSY, DS and FS, categorized as FE |
AI3013 |
Machine Learning |
3 |
Only for APSY, ENVS, and FS, categorized as FE |
AI3033 |
Introduction to Robotics |
3 |
Only for ENVS, categorized as FE |
AI3063 |
Neuroscience in Artificial Intelligence |
3 |
Only for APSY, DS, FS and STAT, categorized as FE |
AI3073 |
Introduction to Bioinformatics |
3 |
Only for ENVS and FS, categorized as FE |
Total |
0 |
||
