How Ramapo’s Computer Science Curriculum is Adapting to AI

AI tools like ChatGPT and GitHub Copilot are changing how software gets built. Students and parents naturally have questions: What does this mean for computer science education? Is programming still worth learning?

At Ramapo, we’re addressing these questions by fundamentally rethinking how we teach computer science. Here’s what we’re doing.

Why Developers Still Matter

AI tools are becoming part of the developer’s toolkit—similar to how calculators became part of math. They handle routine tasks and speed up certain work. But someone still needs to know whether AI-generated code is good, secure, efficient, and actually solves the problem. Someone needs to design systems, make architectural decisions, and fix things when they break.

The industry is learning this the hard way. AI-generated code often creates security vulnerabilities and maintenance problems. Companies need developers who can use AI tools effectively while maintaining quality and deeply understanding their systems. That’s what we’re preparing students for.

Our Curriculum Changes

We’re taking a phased approach that evolves as students progress through the program.

• Foundation Courses (CMPS 147, 148, 231): In Computer Science I & II and Data Structures, we prohibit AI tool use for assignments. Students need to build fundamental programming skills and algorithmic thinking through direct experience. You can’t evaluate AI-generated code if you don’t understand what good code looks like. However, we’re adding exercises where students analyze and critique AI-generated code to understand both its capabilities and limitations.
• Intermediate Courses (CMPS 361, 366, and many 300-level electives): In Software Design and other intermediate courses, we’re introducing controlled AI use. Students may use AI for specific tasks like generating boilerplate code or exploring documentation, but must document all AI use and defend their design decisions in code reviews. Assessment emphasizes in-person examinations, live coding sessions, and complex projects that require architectural thinking.
• Advanced Courses (CMPS 450): In Senior Project, students use AI tools as professional developers do. The focus shifts to building production-quality systems that integrate AI as a component. Students learn to create applications powered by language models, implement safety guardrails, and solve the engineering challenges of production deployment.

AI-Focused Coursework

We’re expanding our AI offerings beyond traditional foundations. Students already take CMPS 331 (Artificial Intelligence) and CMPS 320 (Machine Learning) as electives, which cover core AI concepts and techniques.

We’re now adding two pilot courses focused on applied AI integration:

• Computer Vision (Spring 2026 – Dr. Sourav Dutta): Students learn to build applications that process and understand images and video. The course covers practical implementation using OpenCV and Python, including.
  • Image processing, filtering, and feature detection
  • Edge detection, contour analysis, and object recognition
  • Template matching and real-time tracking from webcam input
  • Convolutional neural networks (CNNs) for image classification
  • Using pretrained models and transfer learning for real-world vision problems
  • Building complete vision-enabled applications with real-world datasets
• Agentic Software Architecture (Summer 2026 – Dr. Scott Frees): This course teaches students to build production-ready AI-powered applications. Students learn to:
  • Integrate large language models into applications
  • Design retrieval-augmented generation systems
  • Implement guardrails and safety mechanisms
  • Build AI agents that can use tools and reason through complex tasks
  • Optimize costs and handle AI system limitations

  This is hands-on work. Students build complete AI-integrated applications and discover that incorporating AI effectively requires sophisticated engineering skills—far beyond simple API calls.

The Bigger Picture

AI isn’t replacing software engineering—it’s changing what software engineers do. The developers who thrive will combine deep technical knowledge with the ability to use AI tools effectively. They’ll design systems, not just code them. They’ll understand both what works and why it works.

Our curriculum prepares students for this reality. We’re teaching fundamental skills that remain valuable as technologies change, while also ensuring students can work effectively with AI tools and build AI-integrated systems.

Questions about our program?
Scott Frees
Convenor: BS in Computer Science, Cybersecurity
Program Director: MS in Computer Science, Data Science, and Applied Mathematics
sfrees@ramapo.edu