Foundations of Data Science Graduate Certificate

Data science student

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Learn about data collection, exploration, manipulation and storage, analysis, and presentation to navigate data-rich workplace environments.
 

About the Certificate

Through its interdisciplinary curriculum, the three-course, 9-unit Foundations of Data Science Graduate Certificate prepares students with a focused amount of foundational data science training as a gateway into a full graduate degree, as an augmenting experience to combine with other graduate degree endeavors or as a stand-alone training to aid them in their data careers. This certificate encompasses foundational work in data science.

Learning Outcomes

Students in the Foundations of Data Science Graduate Certificate will accomplish the following learning outcomes:

  • Demonstrate skills in processing and analyzing data
  • Communicate with and effectively work and interact in teams
  • Demonstrate abilities in analyzing ethical concerns and societal impacts related to data science

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For more information about the Foundations of Data Science Graduate Certificate, complete the form below or contact us at si_admissions@arizona.edu.

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Certificate Requirements

The Foundations of Data Science Graduate Certificate requires 9 units (3 courses) in core informational areas. These courses can overlap entirely with the Master of Science in Information Science if students are dual enrolled. Students can complete the certificate in one to two semesters.

Applicants are expected to have completed undergraduate coursework or have professional experience in programming and statistics. Coursework in calculus is preferred but not required. Applicants should be able to speak to their experience in quantitative and analytical reasoning abilities, as well as experience with math and programming including data structures, analysis of algorithms and linear algebra.

Curriculum

Foundations of Data Science Graduate Certificate students take the following four required courses:

This course presents an overview and understanding of the intractable and pressing ethical issues as well as their related policies in the information fields. Emerging technological developments in relation to public interests and individual well-being are highlighted throughout the course. Special emphasis is placed on case studies and outcomes as well as frameworks for ethical decision-making.

This course will introduce students to the concepts and techniques of data mining for knowledge discovery. It includes methods developed in the fields of statistics, large-scale data analytics, machine learning, pattern recognition, database technology and artificial intelligence for automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns. Topics include understanding varieties of data, data preprocessing, classification, association and correlation rule analysis, cluster analysis, outlier detection, and data mining trends and research frontiers. We will use software packages for data mining, explaining the underlying algorithms and their use and limitations. The course include laboratory exercises, with data mining case studies using data from many different resources such as social networks, linguistics, geo-spatial applications, marketing and/or psychology.

This course provides an overview of the various concepts and skills required for effective data visualization. It presents principles of graphic design, programming skills, and statistical knowledge required to build compelling visualizations that communicate effectively to target audiences. Visualization skills addressed in this course include choosing appropriate colors, shapes, variable mappings, and interactivity based on principles of color perception, pre-attentive processing, and accessibility.

Students may transfer up to 3 units from other accredited institutions with the approval of the certificate advisor. Any course substitutions must be approved in advance by the certificate advisor. Up to 9 units can be shared between the certificate and a University of Arizona master's degree.

Admissions

Application Deadlines

Domestic Applicants

  • Fall Semester: February 15
  • Spring Semester: October 15
  • Summer Semester: March 15

International Applicants

  • Fall Semester: February 15
  • Spring Semester: September 1

How to Apply

To apply, you must complete the University of Arizona Graduate College online application. Follow these steps:

  1. Create a GradApp account
  2. Complete your GradApp profile under "My Account".
  3. Select "Apply to a Program" from the sidebar.
  4. Choose "Graduate Certificate" under application type and then choose the certificate you are interested in.
  5. Choose the semester during which you wish to enter the program.
  6. Your application should now be initiated under "My Active Applications."

Admission Requirements

Applications to our certificate programs are reviewed by our Certificate Coordinator. To be admitted, you must meet the minimum requirements of the UA Graduate College, which include:

  • A bachelor’s degree from the University of Arizona or from an accredited college or university recognized by the University of Arizona
  • A grade point average of 2.75 or higher

View All Graduate Certificate Admissions Information

Policies & Resources

Learn more about resources and policies applicable to graduate certificate students, as well as additional academic resources for new and current students, on our Graduate Certificatate Policies & Procedures page:

View Graduate Certificate Policies & Resources

Ready to transform your future with a School of Information graduate certificate?

Learn more about our graduate certificates by contacting us at si_admissions@arizona.edu, or review the admissions process and begin your application now:

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