Department of Artificial Intelligence
The Department of Artificial Intelligence is dedicated to fortifying academic knowledge and technical skills in artificial intelligence, which is rapidly developing and gaining attention in modern society. Artificial intelligence is a core major that fosters human resources needed for the future era of AI, and the department provides students with fundamental theories and field experiences to cultivate the ability to cope with various challenges in modern society. The department provides students with systematic and in-depth education based on a deep understanding of basic disciplines such as computer science, mathematics, and statistics. In our department, students learn core concepts and skills in areas such as machine learning, deep learning, natural language processing, and robotics. In addition to theoretical knowledge, students develop problem-solving skills through real-world application projects and acquire technical competencies required by the industry. In addition, students can enhance their practical skills through various experiences such as cooperative projects with industrial companies, artificial intelligence competitions, and participation in international academic conferences.
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Courses | Credits | |
---|---|---|
*General Studies (required) Total: 16 credits |
Technical Writing For Science And Technology | 2 |
Critical Thinking and Discussion with Classics | 2 | |
College English(W) | 2 | |
College English(S) | 2 | |
Calculus Ⅰ | 3 | |
Calculus II | 3 | |
UOS Future Design | 1 | |
UOS Career Design | 1 | |
General Studies (elective) Total: 16 credits |
Engineering Grounding | 8 |
*Elementary Major Course Study
*Physics Experiment 1,2 |
8 | |
Major Courses |
Required | 24 |
Elective | 48 | |
Other |
|
24 |
Total |
|
130 |
Course Number |
Course Title | School Year | Semester | Credit | Lecture (hours) |
Practice (hours) |
---|---|---|---|---|---|---|
20003 | STUDY-PLANNING COUNSELINGⅠ | Freshmen | Spring | S/U | 1 | 0 |
20004 | STUDY-PLANNING COUNSELINGⅡ | Fall | S/U | 1 | 0 | |
20040 | Computational Thinking and SW Coding | Spring | 3 | 3 | 0 | |
20048 | Introduction to Statistics | Spring | 3 | 2 | 2 | |
20005 | Problem Solving and Algorithm | Fall | 3 | 3 | 0 | |
20006 | Discrete Mathematics with Applications | Sophomore | Spring | 3 | 3 | 0 |
20007 | Programming Basics and Practice | Spring | 3 | 2 | 2 | |
20008 | Probability and Random Processes | Spring | 3 | 3 | 0 | |
20010 | Algorithm | Spring&Fall | 3 | 3 | 0 | |
20011 | Knowledge Representation and Reasoning | Fall | 3 | 3 | 0 | |
20012 | Machine Learning | Fall | 3 | 2 | 2 | |
20013 | Linear Algebra with Applications | Fall | 3 | 3 | 0 | |
20014 | Understanding and Leveraging Databases | Fall | 3 | 3 | 0 | |
20045 | Statistical Methods for Data Science | Fall | 3 | 3 | 0 | |
20046 | Statistical Inference | Fall | 3 | 0 | 0 | |
20009 | Computer Systems | Junior | Spring | 3 | 0 | 0 |
20015 | Deep Learning | Spring | 3 | 3 | 0 | |
20016 | Data Mining | Spring | 3 | 3 | 0 | |
20017 | Advanced Data Analysis | Spring | 3 | 3 | 0 | |
20018 | Intelligent Robots | Fall | 3 | 3 | 0 | |
20019 | Intelligent Human Computer Interaction | Fall | 3 | 3 | 0 | |
20020 | AI-based Software Engineering | Fall | 3 | 3 | 0 | |
20021 | Pattern Recognition | Fall | 3 | 3 | 0 | |
20041 | Reinforcement Learning | Fall | 3 | 3 | 0 | |
20049 | Programming Languages | Spring | 3 | 3 | 0 | |
20023 | Artificial Intelligence Systems | Senior | Fall | 3 | 2 | 2 |
20024 | Capstone Design 1 | Spring | 3 | 2 | 2 | |
20025 | The Ethics of Artificial Intelligence | Spring&Fall | 3 | 3 | 0 | |
20026 | Natural Language Processing | Fall | 3 | 3 | 0 | |
20027 | Artificial Intelligence Living Lab | Fall | 3 | 2 | 2 | |
20042 | Speech Recognition | Spring | 3 | 0 | 0 | |
20043 | Introduction to Information Theory | Spring | 3 | 3 | 0 | |
20047 | Introduction to Computer Vision | Spring | 3 | 0 | 0 | |
20050 | Analysis of Medical Big Data | Spring | 3 | 3 | 0 | |
20028 | Capstone Design2 | Fall | 3 | 2 | 2 |