Artificial Intelligence
Program Profile
| Name of the program degree |
Bachelor of Engineering Program in Artificial Intelligence |
| Major |
Artificial Intelligence |
| Program duration |
4 Years |
| Total credits |
125 |
Program Structure
| 1. General Education Courses |
24 Credits |
| 1.1 Language Group |
12 Credits |
| 1.2 Humanities and Social Sciences Group |
6 Credits |
| 1.3 Morality and Ethics Development Group |
6 Credits |
| 2. Specific Courses |
95 Credits |
| 2.1 Core Courses |
38 Credits |
| 2.2 Major Specific Courses |
45 Credits |
| 2.2.1 Compulsory Major Courses |
30 Credits |
| 2.2.2 Elective Courses |
15 Credits |
| 2.3 Project, Internship, or Cooperative Education Courses |
12 Credits |
| 3. Free Elective Courses |
(not less than) 6 Credits |
Program Purpose
To cultivate graduates with a comprehensive and in-depth understanding of artificial intelligence theories, models, and applications, enabling them to design, develop, and deploy intelligent systems across various domains, including machine learning, deep learning, natural language processing, computer vision, data science, and AI for the Internet of Things (AIoT).
Student Outcomes
Graduates of this major will possess a strong theoretical and practical foundation in core AI methodologies. They will be able to:
- Design and implement machine learning and deep learning models: Students will have a comprehensive understanding of various machine learning algorithms, advanced models, and deep learning architectures, enabling them to build and apply these to diverse problems.
- Develop and deploy natural language processing (NLP) and computer vision (CV) applications: They will be skilled in processing and analyzing textual and visual data, allowing them to create solutions for language understanding, image recognition, and related tasks.
- Work with large-scale data and apply data science techniques: Students will understand data science principles, including data collection, cleaning, analysis, and interpretation, particularly within the context of big data.
- Integrate AI into real-world systems, including the Internet of Things (IoT): They will be capable of developing AI solutions for connected devices and environments, understanding the challenges and opportunities of AIoT.
- Apply reinforcement learning principles: Students will gain knowledge in training intelligent agents to make optimal decisions through trial and error in dynamic environments.
- Build end-to-end AI solutions: The "End to End Learning" courses suggest an ability to take AI projects from conceptualization to deployment, handling various stages of the development lifecycle.
Career Opportunities
- Machine Learning Engineer
- Deep Learning Engineer
- Data Scientist
- AI Engineer
- Natural Language Processing (NLP) Engineer
- Computer Vision Engineer
- AIoT Engineer
- AI Researcher
- Big Data Engineer
- Reinforcement Learning Engineer
