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PlusOne Program with MS in Artificial Intelligence

The PlusOne Accelerated Master’s Program empowers motivated students like you to start earning your master’s degree while pursuing your undergraduate education. In this program, you can take up to four graduate-level courses and apply them to both your undergraduate and graduate computer science degrees. Gain foundational computer science knowledge and experience while reducing the time it takes to complete a master’s from two years to one.

Program details

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Students pursuing a Khoury College undergraduate degree program, in both core and combined majors, are eligible. Students in combined majors with Khoury College are eligible regardless of their home college affiliation.

Students may complete up to four graduate (master’s) courses as an undergraduate.

  • Only one graduate course may be completed per semester.
  • The remaining required courses must be completed as a master’s student (post-bachelor’s graduation).
  • Minimum 3.0 GPA required to request graduate course enrollment.
    • First-year students cannot take their first graduate-level course during the summer. Please plan to take your first graduate-level course in the fall of your second year at the earliest.
       
  • Students can request enrollment in graduate-level courses via a survey that is emailed out before each semester’s registration period.

Interested students should meet with their advisor no later than their third semester to discuss how the PlusOne pathway will fit into their academic plan and when they plan to complete their first graduate-level course.

Admission requires:

  • Minimum 3.0 GPA, both cumulative and within the major
  • Successful completion of a graduate-level Khoury College course
  • Submission of the online PlusOne Application form:
    • Academic advisors will share the online application form with eligible students
    • Application form should only be submitted after the above requirements are met
    • Admission into the PlusOne program does not guarantee admission into the master’s program upon graduation at the bachelor’s level
  • To continue in the PlusOne program, students must maintain a minimum 3.0 GPA and earn a cumulative 3.0 GPA in all graduate-level CS courses.
  • Students admitted into the PlusOne program maintain undergraduate standing and must continue to request admission into graduate courses each term.
  • Undergraduates are limited to one graduate course per semester, with a limit of four graduate courses (including withdrawals) total during the undergraduate degree. Placement is not guaranteed.
  • Students should confer regularly with their undergraduate academic advisor to ensure proper planning.
  • Students entering a graduate program via the PlusOne pathway are not eligible for the Double Husky Scholarship. If you have additional questions related to tuition or scholarship eligibility, please reach out to Student Financial Services.

Graduate replacements for undergraduate courses

*Students pursuing this pathway must take CS 5800 Algorithms (if they have not already taken CS 3000) and CS 5100 Artificial Intelligence (if they have not already taken CS 4100). Check the course catalog for course descriptions.

Undergraduate Course RequirementGraduate Replacement
CS 3000 Algorithms and DataCS 5800 Algorithms*
CS 4100 Artificial IntelligenceCS 5100 Foundations of Artificial Intelligence*
CS 4150 Game Artificial IntelligenceCS 5150 Game Artificial Intelligence
CS 4180 Reinforcement LearningCS 5180 Reinforcement Learning and Sequential Decision Making
Khoury ElectiveCS 5330 Pattern Recognition and Computer Vision
CS 4610 Robotic Science and SystemsCS 5335 Robotic Science and Systems
IS 4300 Human Computer InteractionCS 5340 Computer/Human Interaction
CS 4120 Natural Language ProcessingCS 6120 Natural Language Processing
Khoury ElectiveCS 6140 Machine Learning
DS 4420 Machine Learning and Data Mining 2DS 5230 Unsupervised Machine Learning and Learning Theory

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Rajagopal Venkatesaramani

Rajagopal Venkatesaramani is an assistant teaching professor at Khoury College. He uses large-scale optimization, machine learning, and game-theoretic framework to enable privacy–utility trade-offs for genomic data sharing.

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