Studyportals
M.Sc. On Campus

Biological Data Science

Arizona State University

12 months
Duration
26460 USD/year
24498 USD/year
12014 USD/year
Unknown
Tuition fee
Unknown
Apply date
Unknown
Start date

About

The Biological Data Science MSc program from Arizona State University provides students with real-world training at the interface of the natural and mathematical sciences. 

Overview

The Biological Data Science MSc program from Arizona State University incorporates multiple levels of experiential learning to ensure students gain critical-thinking skills on top of core competencies. Students will be ready to enter one of the fastest-growing job markets, work with consulting firms and government agencies as well as non-governmental organizations, or go on to seek advanced professional or graduate degrees.

Career Opportunities

The proliferation of big data sets generated in biological science fields has dramatically increased the demand for individuals with the solid skill sets they need to manipulate and interpret this data.

Graduates are ready to enter one of the fastest-growing job markets to work with consulting firms, government agencies as well as nongovernmental organizations, in data science, informatics, data analytics, database development and mathematical modeling of biological systems that are relevant to a variety of industries. They are well suited to employment in positions such as:

  • biomedical researcher
  • bioinformatics data scientist
  • chemical biology data scientist
  • clinical data analyst
  • computational biologist
  • data engineer, data mining engineer
  • database developer
  • fisheries scientist, dairy scientist, animal scientist
  • genomic scientist
  • natural resources data scientist
  • programmer
  • pharmaceutical scientist
  • visualization specialist

Programme Structure

Courses include:

  • Database Systems and Problem Solving in Python
  • Biometry
  • Applied Learning Lab
  • Wet Laboratory Experience
  • Experimental Statistics in Biology
  • Integrative Biology
  • Applied Mathematics Techniques in Biology

Key information

Duration

  • Full-time
    • 12 months

Start dates & application deadlines

More details
  • Spring start date for online option only
  • Fall deadline for online option: August 4

Credits

32 SCH

Delivered

On Campus

Academic requirements

GPA admission requirements GPA
3

Other requirements

General requirements

  • Applicants are eligible to apply to the program if they have earned a bachelor's or master's degree in a related field such as biology, mathematics, statistics or computing, as well as unrelated fields, from a regionally accredited institution.
  • Applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in the last 60 hours of their first bachelor's degree program, or applicants must have a minimum cumulative GPA of 3.00 (scale is 4.00 = "A") in an applicable master's degree program.

All applicants must submit:

  • graduate admission application and application fee
  • official transcripts
  • statement of purpose
  • two letters of recommendation
  • professional resume
  • proof of English proficiency

Tuition Fee

To alway see correct tuition fees
  • International

    26460 USD/year
    Tuition Fee
    Based on the tuition of 26460 USD per year during 12 months.
  • National

    24498 USD/year
    Tuition Fee
    Based on the tuition of 24498 USD per year during 12 months.
  • In-State

    12014 USD/year
    Tuition Fee
    Based on the tuition of 12014 USD per year during 12 months.
  • Online: $10,372 per year

Living costs for Peoria

940 - 1390 USD /month
Living costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

Funding

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Our partners

Biological Data Science
-
Arizona State University

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