Data 8 Major Analysis

An analysis report on which majors are represented in the introductory data science course at UC Berkeley, Data 8.

Archetypes Mapping

An effort to parse student interview responses and establish a categorization methodology for personalities and student intentions in data science

Prototype Classifier

A machine learning approach for scaling up our archetypes to accommodate more data.

Cluster Mappings

Mapping of data science courses offered in diverse fields

Team Members

Team Lead | Subhiksha Mani
Computer Science and Cognitive Science - 2019
I am passionate about data science because it complements my constant curiosity. Data-driven decision-making empowers me to ask important questions and use data to establish meaningful answers. I enjoy using data science to make an impact on students and education at Berkeley.
Fun Fact: In my spare time, I enjoy creatively documenting aspects of life, mainly through photography and digital journaling.

Shriya Vohra
EECS - 2020
I love data science because it allows me to use my programming skills to find interesting patterns and make a difference – especially in education. When I'm not coding, I can be found meme-scrolling, telling stories, and/or traveling the world.

Shruti Rajagopal
Cognitive Science - 2018
I like data science because it can answer question is a broad spectrum of fields that were previously too hard to study. I am excited to provide diverse insights in an efficient and data-driven manner.
Fun fact: I love to cook and bake in my free time.

Smita Balaji
Industrial Engineering and Operations Research - 2019
I find studying data science to be important because of its interdisciplinary and applicable nature. Any major, and any industry can utilize fundamentals tools to understand any sort of data set.