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Allied Health & Medical Assisting Services at Manhattan School of Computer Technology

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Allied Health & Medical Assisting Services at Manhattan School of Computer Technology

If you are interested in studying allied health and medical assisting services, you may want to check out the program at Manhattan School of Computer Technology. The following information will help you decide if it is a good fit for you.

Manhattan School of Computer Technology is located in Brooklyn,, New York and has a total student population of 392.

Want to know more about the career opportunities in this field? Check out the Careers in Allied Health & Medical Assisting Services section at the bottom of this page.

Manhattan School of Computer Technology Allied Health & Medical Assisting Services Degrees Available

  • Undergrad Certificate in Medical Assisting (1 - 4 Years)

Manhattan School of Computer Technology Allied Health & Medical Assisting Services Rankings

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Concentrations Within Allied Health & Medical Assisting Services

If you plan to be a medical assisting major, you may want to focus your studies on one of the following concentrations. The table shows all degrees awarded in this field awarded for all degree levels at Manhattan School of Computer Technology. A concentration may not be available for your level.

Concentration Annual Degrees Awarded

Careers That Medical Assisting Grads May Go Into

A degree in medical assisting can lead to the following careers. Since job numbers and average salaries can vary by geographic location, we have only included the numbers for NY, the home state for Manhattan School of Computer Technology.

Occupation Jobs in NY Average Salary in NY
Medical Assistants 26,080 $37,560
Health Specialties Professors 22,170 $127,230
Pharmacy Technicians 19,320 $34,640
Physician Assistants 12,060 $117,000
Healthcare Support Workers 6,360 $37,380

References

*The racial-ethnic minorities count is calculated by taking the total number of students and subtracting white students, international students, and students whose race/ethnicity was unknown. This number is then divided by the total number of students at the school to obtain the racial-ethnic minorities percentage.

More about our data sources and methodologies.

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