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Data Fluency

The Certificate in Data Fluency provides a formal pathway for undergraduates in concentrations other than applied mathematics, computational biology, computer science, math, and statistics who wish to gain fluency and facility with the tools of data science. The driving intellectual question is how we can infer meaning from data whilst avoiding false predictions. The required experiential learning component provides students with the opportunity to apply their data-science skills in applied settings, engage in research that uses data science, teach data science as an undergraduate teaching assistant, or undertake an internship that has a substantive data-science component.

As with all undergraduate certificates, the certificate has the following requirements:

  • Students may not earn more than one certificate and may only have one declared concentration.
  • Students must be enrolled in or have completed at least two courses toward the certificate at the time they declare in ASK.
  • No more than one course may count toward your concentration and the certificate.
  • Students may declare in ASK no earlier than the beginning of the fifth semester and must declare no later than the last day of classes of the antepenultimate (typically the sixth) semester, in order to facilitate planning for the capstone or other experiential learning opportunity.
  • Students must submit a proposal for their experiential learning opportunity by the end of the sixth semester.

Excluded Concentrations: Applied Mathematics, Computational Biology, Computer Science, Mathematics, and Statistics (including joint concentrations in these areas).

For more information on the Certificate in Data Fluency, please visit the Data Science Institute website.

Certificate Requirements

Core Courses:
DATA 0080Data, Ethics and Society1
CSCI 0111Computing Foundations: Data1
or CSCI 0150 Introduction to Object-Oriented Programming and Computer Science
or CSCI 0170 Computer Science: An Integrated Introduction
or CSCI 0190 Accelerated Introduction to Computer Science
or CLPS 0950 Introduction to programming
DATA 0200Data Science Fluency1
Elective Course: Select one follow-up Applied Math, Biostatistics, Computer Science or domain-specific course with a significant data component from the following list (or another course with approval from the certificate advisor):1
Introduction to Geographic Information Systems and Spatial Analysis
Statistical Inference I
Statistical Analysis of Biological Data
Methods in Informatics and Data Science for Health
Survey of Biomedical Informatics
Statistical Methods
Computational Methods for Mind, Brain and Behavior
Visualizing Information
Advanced Introduction to Probability for Computing and Data Science
Deep Learning
Data Science
Data Science Fellows 1
Introduction to Econometrics
Big Data
Applied Statistics for Ed Research and Policy Analysis
Introduction to Environmental GIS
Introduction to Geographic Information Systems for Environmental Applications
Global Environmental Remote Sensing
Probability
Seminar in Electronic Music: Real-Time Systems
Essentials of Data Analysis
Principles of Biostatistics and Data Analysis
Methods of Social Research
Introductory Statistics for Social Research
Principles and Methods of Geographic Information Systems
Capstone:0-1
The required experiential learning component provides students with the opportunity to apply their data-science skills in their concentration, engage in research that uses data science, teach data science as UTAs, or undertake an internship that has a data-science component. The capstone may be completed for credit via an independent study course or not for credit. 2
Options for fulfilling this requirement include:
1. Participate in a Brown University credit experience (i.e. independent study).
2. Participate in a non-credit experience: summer Internship; TA for data-related course; work with a local organization on a data-related project. A 10-12 page reflective paper is required for this option.
3. Be a Data Science Fellow. 1
Total Credits4-5
1

Students may complete DATA 1150 and the concurrent Data Science Fellows project to fulfill both the elective and experiential components of the certificate.  

2

Students must submit a proposal for their experiential component by the end of the sixth semester.