Diagram showing natural language processing as part of artificial intelligence, connected to machine learning and other areas of computer science
Natural language processing is one part of artificial intelligence, and it now sits near the center of how many people experience AI tools.

One of the questions students are asking right now is also one of the most reasonable.

Should I still study computer science if AI can write code?

I recently wrote a piece for CU Boulder Online about that question, with a focus on artificial intelligence, natural language processing, large language models, and the future of computer science careers.

The short version is that computer science is not disappearing.

The work is changing.

Natural language processing used to feel like a specialized area of artificial intelligence. Now it shows up in chatbots, search engines, coding assistants, summarization tools, translation systems, tutoring tools, workplace automation, and everyday software.

That shift changes what students need to learn.

It does not remove the need for strong foundations. Students still need programming, algorithms, data structures, databases, systems, software engineering, and mathematical reasoning. They also need enough AI literacy to use tools carefully, evaluate outputs, understand limits, and connect technical systems to real problems.

That is especially relevant for post-baccalaureate students. Many students in CU Boulder’s Applied Computer Science Post-Baccalaureate program already bring knowledge from another field. In an AI-shaped software world, that earlier experience can become part of their technical strength.

You can read the full CU Boulder Online article here:

AI, Natural Language Processing and the Future of Computer Science Careers

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