B.Sc. in Artificial Intelligence
B.Sc. in Artificial Intelligence (AI)
The bachelor's in Artificial Intelligence trains students to design, analyze, and deploy modern AI systems from first principles. The curriculum is designed to be rigorous and comprehensive, coupling strong foundations in computing, algorithms, and mathematical reasoning with a cohesive AI core. Students learn to formalize problems, select and justify model classes, derive and interpret optimization and generalization results, and reason quantitatively about error, uncertainty, and obustness. Emphasis is placed on the full stack of AI—data pipelines, model training and evaluation, systems performance, security boundaries, and human-centered considerations — so that graduates can build solutions that are not only accurate, but reliable, efficient, and safe.
Instruction follows a lecture and project-based approach that demands reproducible experimentation, disciplined use of version control, and transparent reporting (data/model cards, calibration, ablations, and limitations). High-impact learning is built in: students engage with research labs and industry partners, pursue internships or undergraduate research, and culminate their studies in a capstone where teams deliver an end-to-end system that meets explicit acceptance criteria for performance, reliability, and documentation.
Graduates are prepared for roles that require real technical depth (AI/ML engineer, computer vision/NLP engineer, AI product and systems developer) as well as for advanced study. The program’s hallmark is its combination of mathematical rigor, algorithmic depth, and systems-level engineering, producing graduates who can scope meaningful problems, defend design choices with evidence, evaluate models with statistical and computational rigor, communicate clearly to stakeholders, and uphold professional, ethical, and security standards in fast-evolving AI environments.
| Course Number | Course Title | Hours |
|---|---|---|
| AI 4610 | Advanced Computer Vision | 3 |
| AI 4620 | AI in Autonomous Systems | 3 |
| AI 4630 | Efficient Neural Networks | 3 |
| AI 4640 | Neuromorphic Computing | 3 |
| AI 2700 | Special Topics in AI | 3 |
| AI 4700 | Special Topics in AI | 3 |
| AI 4200 | Independent Study in AI | 3 |
| AI 3220 | Research in AI | 3 |
| AI 4220 | Advanced Research in AI | 3 |
| AI 4240 | Internship in AI | 3 |
The degree is offered on campus with standard scheduling.
Students in the AI major must have reliable access to a laptop capable of running current AI toolchains (Python, Jupyter, modern deep-learning frameworks) and connecting to LSU resources.
Course-specific software will be provided or specified by the instructor.
Admission Requirements
Admission to the B.Sc. in Artificial Intelligence's curriculum requires that a student be admissible to the College of Engineering prior to enrolling in any computer science (CSC) or artificial intelligence (AI) courses numbered above 2000.
Critical Requirements:
- Sem 1: "C" or better in both ENGL 1001 and MATH 1550
- Sem 2: “C” or better in ENGL 2000, ECON 2030, and MATH 1552
- Sem 3: “C” or better in MATH 2057; Admission to the College
- Sem 4: “C” or better in MATH 2085
- Sem 5: “C” or better in MATH 2090
Artificial Intelligence majors must earn a grade of “C” or better in all computer science (CSC), artificial intelligence (AI), and mathematics (MATH) courses before registering for any subsequent courses that require the above as prerequisites.
At least 30 of the hours required for this degree must be taken at the 3000/4000-level. See the LSU General Catalog for information on University, College, major, and minor residency requirements.