UT Austin LIN 313:
Language and Computers
Fall 2025

By the end of this course, students will be able to:

• You will be able to explain what kinds of problems have to be solved in order for computers to do useful things with language. In order to train a computer to perform a human language task, we first have to understand something about how human language works and what kinds of problems need to be solved.
• You will learn how to approach tasks from a computational perspective. This is not a programming class, but through class exercises and homework, you will gain experience thinking like a computer scientist and about how a computer scientist would go about solving problems in human language.
• You will gain insight into the technology that underlies a wide variety of human language technologies, from spell checkers to search engines to dialogue systems.
• You will gain experience thinking about data. Data science is one of the fastest growing fields for graduating college students. Throughout this class, we will think about the nature of experiments and data.
• You will gain a better understanding of the ethical considerations around work in computational linguistics. We will spend time not just on the primary research, but on thinking about the higher-order ethical and practical considerations that impact computational linguistics as a field.

• Class Canvas page
• Class inspiration page
• UT Instapoll
• Sage Tutor
• UT Forum for AI (FAI): Upcoming talks
• Class Concept Map

Readings will draw from various sources. Everything will be digitally available through Canvas, the UT library, or this website. We will draw pretty heavily from two books in particular.

• Artificial Intelligence: A Guide for Humans (Farrar Girou, & Strauss 2019) by cognitive scientist Melanie Mitchell (Santa Fe Institute). A very accessible, math-free introduction to AI that doesn't shy away from the details. Published just shy of the LLM era, it's a prescient foretelling of what was to come. It grounds the discourse around the present 'AI Spring' in a century of boom and bust cycles and connects today's questions to long-running debates about the nature of human intelligence.
• Speech and Language Processing By Dan Jurafsky and James Martin (UC Boulder). The current gold standard NLP textbook. This text is written for computer science students. It is dense, and gets technical at times. Therefore, where Mitchell covers a topic I will assign that chapter instead, (but I'll still link you to J&M for optional further reading. Note: Make sure you use the copy I link you to which is the most up to date draft of 3rd edition.

The 'math free' Mitchell isn't dumbed down–it's deeper. Mitchell's ability to explain technical topics without resorting to esoteric symbols and formalisms is rare and invaluable. The more you (as a student) are able to explain technical topics in terms of concrete examples and experience, the stronger the foundation of intuition you build, and the better you are set up for creative reasoning about those topics. Use the mitchell to understand what is happening. Use J&M for nuts and bolts.

***The schedule changes frequently. Check this page regularly for updates.***

Unit 1: Language as Information

Unit 2: Meaning & Classification

Unit 3: Neural Networks & Deep Learning

Unit 4: Large Language Models & Society

Finals Week

Your final grade will be based on the following components. There will be ample opportunity throughout the semester to get extra credit in different ways: adding to the online discussion, attending some of the many AI talks that happen on campus, or working on an independent project.

Academic Integrity

Each student in the course is expected to abide by the University of Texas Honor Code: "As a student of The University of Texas at Austin, I shall abide by the core values of the University and uphold academic integrity." Plagiarism is taken very seriously at UT. Therefore, if you use words or ideas that are not your own (or that you have used in previous class), you must cite your sources. Otherwise you will be guilty of plagiarism and subject to academic disciplinary action, including failure of the course. You are responsible for understanding UT's Academic Honesty and the University Honor Code which can be found at the following web address: https://deanofstudents.utexas.edu/conduct/standardsofconduct.php

Sharing of Course Materials is Prohibited

No materials used in this class, including, but not limited to, lecture hand-outs, videos, assessments (quizzes, exams, papers, projects, homework assignments), in-class materials, review sheets, and additional problem sets, may be shared online or with anyone outside of the class unless you have my explicit, written permission. Unauthorized sharing of materials promotes cheating. It is a violation of the University's Student Honor Code and an act of academic dishonesty. I am well aware of the sites used for sharing materials, and any materials found online that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.

Notice about missed work due to religious holy days

A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.

FERPA and Class Recordings

Class recordings are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form. Violation of this restriction by a student could lead to Student Misconduct proceedings.

Academic dishonesty policy

You are encouraged to discuss assignments with classmates. But all written work must be your own. Students caught cheating will automatically fail the course. If in doubt, ask the instructor.

Services for Students with Disabilities

The university is committed to creating an accessible and inclusive learning environment consistent with university policy and federal and state law. Please let me know if you experience any barriers to learning so I can work with you to ensure you have equal opportunity to participate fully in this course. If you are a student with a disability, or think you may have a disability, and need accommodations please contact Services for Students with Disabilities (SSD). Please refer to SSD's website for contact and more information: http://diversity.utexas.edu/disability/. If you are already registered with SSD, please deliver your Accommodation Letter to me as early as possible in the semester so we can discuss your approved accommodations and needs in this course.

Counseling and Mental Health Center

The Counseling and Mental Health Center serves UT's diverse campus community by providing high quality, innovative and culturally informed mental health programs and services that enhance and support students' well-being, academic and life goals. To learn more about your counseling and mental health options, call CMHC at (512) 471-3515.

If you are experiencing a mental health crisis, call the CMHC Crisis Line 24/7 at (512) 471-2255.

The Sanger Learning Center

Did you know that more than one-third of UT undergraduate students use the Sanger Learning Center each year to improve their academic performance? All students are welcome to take advantage of Sanger Center's classes and workshops, private learning specialist appointments, peer academic coaching, and tutoring for more than 70 courses in 15 different subject areas. For more information, please visit http://www.utexas.edu/ugs/slc or call 512-471-3614 (JES A332).

Additional Resources

• Undergraduate Writing Center: http://uwc.utexas.edu/
• Libraries: http://www.lib.utexas.edu/
• ITS: http://www.utexas.edu/its/
• Emergency Services: http://deanofstudents.utexas.edu/emergency/