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2. The student is able to assess what sensor, hardware, control, algorithm components are suitable given a particular AI problem in industry or academia.
3. The student can apply the knowledge and skills to implement respective components and integrate them into a full array of solutions to solve the problem.
4. The student can interpret the results and evaluate the effectiveness of the solution and make revisions and improvements to create better solutions.
5. Using AI, the student can design solutions to real world applications under practical constraints.
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Engineering Artificial Intelligence M.S.
LEARNING OBJECTIVES
1. The student can demonstrate knowledge and skills in AI related fields that go beyond pure algorithms and software to include sensors, hardware, control and applications.2. The student is able to assess what sensor, hardware, control, algorithm components are suitable given a particular AI problem in industry or academia.
3. The student can apply the knowledge and skills to implement respective components and integrate them into a full array of solutions to solve the problem.
4. The student can interpret the results and evaluate the effectiveness of the solution and make revisions and improvements to create better solutions.
5. Using AI, the student can design solutions to real world applications under practical constraints.
SUCCESS RATES
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3-year graduation rate
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Avg. years to degree
MEDIAN EARNINGS
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10 years after graduation
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5 years after graduation
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1 year after graduation
PLACEMENT2 years after graduation
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Working in New York
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Continuing Education