Engineering (Professional Program: MEng)
Admission Requirements
- Prior Degrees Baccalaureate degree in engineering or a closely related field, such as biology, chemistry, computer science, mathematics, or physics, from a regionally accredited college or university.
- Prerequisite Coursework For non-engineering or computer science majors, applicants must have calculus 1 through calculus 3 (which is the equivalent to MATH 180, MATH 181, and MATH 210 at UIC) and the equivalent of 10 semester hours in sciences, all with a grade of C or better.
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Computer Programming Languages It is strongly recommended that students have at least one course in programming. Python is the recommended language for this program and Python courses can be found online to be completed before starting the program.
- Grade Point Average A cumulative grade point average of 3.00/4.00 for the final 60 semester hours (or 90 quarter hours) of undergraduate study.
- Transcripts Registrar-issued transcripts (copies) from all colleges or universities attended. Transcripts must state degree conferred from awarding institution.
- Work Experience Two years or more of post-bachelor's professional work experience is required.
- Resume Required.
- Letters of Recommendation Two required.
- International Students Refer to International Requirements.
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Minimum English Competency Test Scores (for international applicants) Applicants whose native language is not English are required to take an English competency test. Minimum required scores are:
- TOEFL iBT 80, with subscores of Reading 19, Listening 17, Speaking 20, and Writing 21, OR,
- IELTS Academic 6.5, with 6.0 in each of the four subscores, OR,
- PTE-Academic 54, with subscores of Reading 51, Listening 47, Speaking 53, and Writing 56.
Degree Requirements
- Minimum Semester Hours Required 36.
- Coursework Nine courses, totaling 36 hours.
Code | Title | Hours |
---|---|---|
Required Courses | ||
Engineering Law | ||
Engineering Management | ||
Math Fundamentals for AI Engineers and Data Scientists | ||
Innovation Tools and Methods | ||
Image Analysis and Computer Vision I | ||
Seminar | ||
Artificial Intelligence I | ||
Introduction to Machine Learning | ||
Natural Language Processing |