The Master's in Intelligent Information Systems degree focuses on recognizing and extracting meaning from text, spoken language and video. As an MIIS student, you’ll receive the department’s deepest exposure to content analysis and machine learning. In addition to completing the program’s coursework, you’ll work on directed study projects with your faculty advisor for two semesters; participate in a summer internship; and collaborate with your peers on a semester-long, group-oriented capstone project. This combination of classroom instruction, professional experience, and using new skills in significant projects with world-class colleagues will help prepare you for a successful career in industry or government. Our alumni have gone on to exciting careers at places like Apple, IBM and Google, and most have job offers within six weeks of graduation.

The Intelligent Information Systems degree offers students the flexibility to create their own course of study in consultation with their advisor.

MIIS students gain three types of practical experience: software development supervised by their advisor (24 units equivalent to two courses); a summer internship (which can be waived for students that have sufficient prior professional experience); and a capstone project executed in a group of peers (42 units equivalent to three 12-unit courses and one 6-unit course). This combination is proven to help IIS students to broaden their skills quickly. The MIIS degree is offered in two options:

Option 1. Standard MIIS degree (MIIS-16) - A 16-month track that is completed in three academic semesters (fall, spring, fall) and a summer internship.

Option 2. MIIS: Advanced Study degree (MIIS-21) - A 21-month track that is completed in four academic semesters (fall, spring, fall, spring) and a summer internship.

MIIS: Advanced Study track offers an in-depth degree in one of the following areas of concentration:

• Human Language for Language Technologies
• Language Technology Application
• Machine Learning for Language Technologies

Part-time education option is available in some cases.

MIIS-16 students must take at least 84 units (typically 7 courses) of qualifying and elective courses that satisfy human language, machine learning, and language technology applications breadth requirements. MIIS-21 students have to take at least two more courses from the selected concentration area to satisfy their degree requirements, making it total of 108 units (typically 9 courses) of qualifying and elective courses, that also satisfy breadth requirements.

For a full list of requirements, read the MIIS Handbook.

MIIS-16 

Example Course of Study #1

This schedule would satisfy course requirements for a student interested in text mining, text analytics and question-answering systems.

Fall 1	Spring	Summer	Fall 2
Machine Learning Search Engines Design and Engineering of Intelligent Systems\ Directed Study	Language and Statistics Natural Language Processing Question Answering Directed Study MIIS Capstone Planning Seminar	Internship	Machine Learning for Text Mining MIIS Capstone Project

Example Course of Study #2

This schedule would satisfy course requirements for a student interested in voice-based computer applications.

Fall 1	Spring	Summer	Fall 2
Machine Learning Algorithms for NLP Speech Recognition and Understanding Directed Study	Applied Machine Learning Competitive Engineering Design and Implementation of Speech Recognition Systems Directed Study MIIS Capstone Planning Seminar	Internship	Conversational Interfaces MIIS Capstone Project

Example Course of Study #3

This example would satisfy course requirements for a student interested in text mining, text analytics and question-answering systems who has petitioned to have the summer internship waived.

Fall 1	Spring	Summer
Search Engines Analysis of Social Media Design and Engineering of Intelligent Systems Directed Study	Machine Learning Natural Language Processing Question Answering Directed Study MIIS Capstone Planning Seminar	Academic Research Practices and Scientific Communities MIIS Capstone Project

 

MIIS-21

Example Course of Study #1

This schedule would satisfy course requirements for a student interested in deepening their expertise in Machine Learning area of concentration.

Fall 1	Spring 1	Summer	Fall 2	Spring 2
Search Engines Algorithms for NLP Intro to ML (MLD) MIIS Directed Study	Question Answering Intro to Deep Learning MIIS Capstone Planning Seminar MIIS Directed Study	Internship	MIIS Capstone Project Applied ML	ML for Text Mining ML for Signal Processing Elective

 

Example Course of Study #2

This schedule would satisfy course requirements for a student interested in deepening their expertise in Language Technology Applications area of concentration.

Fall 1	Spring 1	Summer	Fall 2	Spring 2
Search Engines Algorithms for NLP Intro to ML (MLD) MIIS Directed Study	Question Answering Intro to Deep Learning MIIS Capstone Planning Seminar MIIS Directed Study	Internship	MIIS Capstone Project Machine Translation	Comp Semantics for NLP Neural Networks for NLP Elective

 

Example Course of Study #3

This example would satisfy course requirements for a student interested in deepening their expertise in Human Language area of concentration

Fall 1	Spring 1	Summer	Fall 2	Spring 2
Natural Language Processing Algorithms for NLP Intro to ML (MLD) MIIS Directed Study	Question Answering Intro to Deep Learning MIIS Capstone Planning Seminar MIIS Directed Study	Internship	MIIS Capstone Project Language and Statistics	Comp Semantics for NLP ML for Signal Processing Elective

 

For a complete breakdown of curriculum and requirements, read the MIIS Handbook.

Carnegie Mellon's School of Computer Science has a centralized online application process. Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by the application deadline. Incomplete applications will not be considered. The application period for Fall 2024 is now closed. Information about the Fall 2025 admissions cycle will be available in summer 2024.

*Please note, we no longer require mailed, hard versions of transcripts or test scores at the time of application. Do not mail anything to the admissions office. If you are accepted to a program, you will be given instruction to then mail your materials.

Application Deadlines

Applications open on September 4, 2024

Early deadline - November 20, 2024 (3pm EST)

Final deadline - December 11, 2024 (3pm EST)

Fee Waivers

Fee waivers may be available in cases of financial hardship, or for participants in select "pipeline" programs. For more information, please refer to the School of Computer Science Fee Waiver page.

Requirements

The School of Computer Science requires the following for all Master's applications.

• GRE scores: MIIS applicants must submit their GRE scores. The scores must be less than five years old. The GRE Subject Test is not required, but is recommended. Our Institution Code is 2074; Department Code is 0402.
• TOEFL scores: Required if English is not your native language. No exceptions. If you are currently working on or have received a bachelor's and/or a master's degree in the U.S. and your native language is not English, you may submit an expired test score up to five years old. TOEFL scores taken before August 20, 2016, will not be accepted. (While the TOEFL is preferred, the IELTS or Duolingo tests may also be submitted.) Successful applicants will have a minimum TOEFL score of 100. Our Institution Code is 4256; the Department Code is 78.
• Official transcripts from each university you have attended, regardless of whether you received your degree there.
• Current resume.
• Statement of Purpose.
• Three letters of recommendation.

For more details on these requirements, please see the SCS Master's Admissions page.

In addition to the SCS guidelines, the MIIS requires:

• A short (1-3 minute) video of yourself. There will be a prompt question that you will respond to. You will have three attempts.

No incomplete applications will be eligible for consideration.

For specific application/admissions questions, please contact Brianna Eriksen.

For more information about the MIIS program, contact Brianna Freeman.