Flatiron School: Full-time, 15-Week Data Science Immersive in New York City, 2018-19

Subjects covered:

  • Data cleaning & gathering: Python, Pandas, NumPy, SQL

  • Visualization with Matplotlib & Seaborn

  • Frequentist & Bayesian statistical methods

  • Regression (linear, multi-variate, logistic)

  • Hypothesis & A/B testing

  • Supervised & unsupervised machine learning methods for classification, clustering

  • Time series analysis

  • Regexs & NLP

  • PySpark & big data

  • Deep learning

University of Washington: M.L.I.S., beta phi mu, 2017

Coursework included:

  • Introduction to Data Science (programming in R)

  • Beginner Front-end Web Development (JavaScript, HTML, CSS)

  • Information Retrieval Systems (search algorithms, SEO)

  • Information Structures Using XML (XSLT, XSD, etc.)

  • Independent Study: What Makes 'Quality' Metadata

  • Digital Preservation

  • Qualitative Research Practicum: Disaster Response Information Management

  • Construction of Indexing Languages

  • Research, Assessment, and Design

  • Information Behavior

  • Management of Information Organizations

  • Instructional and Training Strategies for Information Professionals

Reed College: B.A., Classics, 2013

Awards:

Professional Development Grant (Visual Resources Association Foundation, 2016)

Digital Library Federation Students and New Professionals Forum Fellowship (Digital Library Federation, 2016)

iSchool Jones Information Fellowship (University of Washington, 2015)

Ruby-Lankford Grant for Faculty-Student Collaborative Research in the Humanities (Reed College, 2012)

Commendation for Academic Excellence (Reed College, 2012 & 2013)

Opportunity Grant (Reed College, 2012 & 2013)

Certificates, Extracurricular Courses:

Statistical Foundations for Data Science and Machine Learning (Metis, 2017)

JavaScript Jumpstart (Fullstack Academy, 2016)

Certificate of Achievement: Privacy Literacy (Infopeople, 2016)