AI and ML Education During BS in Computer Science at UL Lafayette
At the University of Louisiana at Lafayette, we believe that preparing tomorrow’s artificial intelligence (AI) and machine learning (ML) innovators demands more than teaching algorithms alone. It requires fostering a deep understanding of how intelligence works, learning to build and evaluate complex intelligent systems, and cultivating the foresight to ensure these technologies serve humanity responsibly.
Our undergraduate computing programs give students the foundations they need to excel in this dynamic field. Through an integrated journey that blends rigorous theory, hands-on engineering, and thoughtful exploration of AI’s societal impacts, students develop the skills and perspectives essential for the AI and ML careers of tomorrow.
The following table highlights key courses in our curriculum and their specific roles in shaping a well-rounded AI/ML education:
| Course | Course Title | Focus and Role in AI/ML Education |
|---|---|---|
| CMPS 150 | Introduction to CMPS | Foundations in programming (Python), problem-solving, and core computing concepts. |
| CMPS 260 | Intro to Data Structures & Software Design | Object-oriented design (Java), software systems modeling, AI decision-making basics. |
| CMPS 261 | Advanced Data Structures & Software Design | Mastery of data structures (graphs, trees), performance analysis for scalable AI algorithms. |
| CMPS 310 | Computers in Society | Ethical, legal, and societal impacts of AI, including bias and workforce transformation. |
| CMPS 320 | Introduction to AI & ML | Fundamentals of AI/ML (search, reasoning, planning), supervised & unsupervised learning, intro to Natural Language Processing (NLP). |
| CMPS 340 | Design and Analysis of Algorithms | Efficiency, recursion, dynamic programming, graph algorithms—algorithmic reasoning. |
| CMPS 341 | Foundations of Computer Science | Logic, sets, proof techniques—clear and rigorous thinking for AI system design. |
| CMPS 357 | Accelerated Software Development Using AI Tools | AI-assisted software engineering (prototyping, testing), critical evaluation of AI-generated code. |
| CMPS 420 | Artificial Intelligence | Agent-based AI, decision-making, advanced planning, game-playing, knowledge representation, deep learning. |
| CMPS 422 | Machine Learning | Advanced ML: model design in Python, supervised/unsupervised methods, bias-variance, validation, dimensionality reduction. |
| CMPS 455 | Operating Systems | Applied ML for CPU scheduler prediction, real-world AI in system optimization. |
| CMPS 460 | Database Management Systems | Application of LLMs and AI chatbots, enhancing SQL and database task performance. |
| CMPS 490 | Senior Project | Capstone: student-led AI/ML projects with mentorship, showcasing design, implementation, and creativity. |
Graduates of UL Lafayette’s computing programs emerge as well-rounded, forward-thinking professionals, ready to thrive as AI engineers, data scientists, software developers, or advanced researchers. They stand out not only for their technical expertise but for a principled, human-centered perspective, prepared to lead in a world increasingly shaped by intelligent systems.
Our graduates put these skills to work across Louisiana and beyond. Locally, they’ve helped drive innovation at CGI, Perficient, Techneaux, Stuller, McIlhenny, IBM in Baton Rouge, and GE in New Orleans. Others have launched careers with global leaders like Google, Microsoft, Facebook, HP, and Intel, applying AI and ML to tackle some of today’s most pressing challenges. Many also contribute their expertise at national laboratories and across U.S. federal and state agencies, bringing intelligent systems to critical public and research missions.
Whether your goal is to push the boundaries of machine learning, build systems that adapt and learn on their own, or ensure tomorrow’s AI technologies are fair and transparent, you’ll find your launchpad here.