Human Language Technology
Master of Science
Quick Facts
Top 1%
of all Higher-Ed
Institutions
- Center for World University Rankings, 2024
#1
In Best Value Among
Arizona's Public Universities
- Payscale, 2024
Discover the future of language and technology with our interdisciplinary Master's in Human Language Technology (HLT) at the University of Arizona Online.
Why Choose Our HLT Program?
Balanced, Practical Curriculum: Explore a dynamic blend of linguistics, computational linguistics, and practical skills. Our program covers everything from speech recognition and machine translation to web search engine technology and more, with a strong emphasis on artificial intelligence (AI) applications, including (large language models) LLMs.
High Demand for HLT and AI Professionals: The fields of HLT and AI are rapidly expanding, with a growing need for skilled professionals like programmers, computational linguists, data scientists, and natural language processing engineers. Our graduates are prepared for diverse careers across industries, not just academia.
Real-World Experience: A highlight of our program is a hands-on internship where students apply what they've learned in a real-world NLP project. Our students have completed their internships with top companies, including Lockheed Martin, Intel, Raytheon, IBM, Motorola, and tech start-ups. With a variety of options to document your internship, you'll be well-prepared whether your plans after graduation include academia or industry.
Program Highlights
- Flexible Online Learning: Designed for working professionals, our program is delivered entirely online, with courses available in fall, spring, and summer. Study at your own pace with asynchronous content and weekly deadlines. Each course in the program is delivered over 7.5 weeks.
- Interdisciplinary Focus: Our program includes linguistics, computer science, AI, and more. We welcome students from various backgrounds, provided they have a passion for language and sufficient programming proficiency in Python.
- Career-Oriented: With more job opportunities in the industry than in traditional academia, our program prepares you for a competitive workforce. You’ll be equipped with the skills needed to excel in roles that bridge language and
Eligibility: An undergraduate major in linguistics or computer science is not required, but applicants should have some programming experience, preferably Python, and some understanding of language.
*Residents of some U.S. Territories may not be eligible. Please see our Eligibility & State Authorization page for more information.
The curriculum for this program includes:
Receive an introduction to human language technology (HLT). Content includes a combination of theoretical and applied topics including tokenization across languages, n-grams, word representations, basic probability theory, introductory programming and version control.
Get a hands-on introduction to text classification, word embeddings, sequence labeling, parsing and an examination of analogical reasoning using word embeddings.
Explore the fundamentals of formal language theory, syntactic and semantic processing and the place of world knowledge in natural language processing.
Outcomes
Skills
Earning your Master of Science in Human Language Technology will build core skills, including:
- Computational Linguistics statistical & symbolic methods
- Natural Language Processing
- Neural Network-based models
- Speech Technology
- Text Retrieval & information extraction
Potential Career Paths
Graduates of the Human Language Technology program will be prepared to pursue the following career fields:
Student Quote
“My program gave me so many fundamentals for statistics and linguistic program design, which are essential to understanding the behind-the-scenes operation of the tools I’m using… People coming out of the HLT program have the opportunity to be highly valuable citizens of the world — to help society navigate through the rapid changes that are happening now and coming.” – Trevor Sullivan, a 2017 HLT alum and senior artificial intelligence conversational engineer with a large financial services company.
