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More than Just Numbers: Computational Sciences at Minerva

by Rory Foulger | Class of 2019

June 22, 2018

I never imagined that I would study Computational Sciences (CS) in college. I grew up in the United Kingdom (UK) where students have to narrow down their academic focus very early on in high school, and I was distinctly a humanities student — I loved studying English literature, philosophy, ancient history, theatre, and creative writing. After taking a gap year in Norway, I studied education at a traditional university in the UK before deciding to transfer to Minerva, an institution I knew would challenge me in completely new ways.

Initially, I intended to major in Arts and Humanities, since I had an interest in both philosophy and psychology. But Minerva’s first-year curriculum, which teaches students how to think critically and creatively, inspired me to broaden my academic interests and challenge myself by pursuing CS.

In order to prepare for this shift in my studies, I had to learn a lot about the field of CS by myself. The summer before my first year at Minerva, I taught myself the programming languages Python and R, read books on computational thinking, sharpened my statistical knowledge, and relearned all the math I’d forgotten in the three years since I finished high school.

Once I arrived at Minerva, I met my amazing academic advisor, who saw my potential in CS and encouraged me to pursue analytical subjects. CS is taught very differently at Minerva compared to other university programs. My younger brother is currently in his first year of studying CS at a traditional university in the United Kingdom, and our experiences have been quite divergent. There are some advantages to his degree; he spends a lot of time in labs learning robotics and game design in a really fun way, and he is taught programming languages in detail, guided through each step from beginning to end.

As for me, the Minerva curriculum has prepared me to take on challenges, even those that I haven’t been explicitly taught. For example, I can find documentation for fragments of code to help find a solution, and I know how to use resources like Stack Overflow to get help from the coding community. My classmates and I learn a lot of the material by ourselves because most introductory information is easily accessible on the internet. Our classes focus on more advanced material and real-life application. In my second year, I explored topics like genetic matching and techniques to prove causation that many students at traditional schools will not be introduced to until graduate school.

Yes, academics at Minerva are hard — but the challenge has been worth it; one of the most valuable takeaways is the shift in the way I think. I’ve learned how to use a variety of resources to work through a problem. I’ve learned how to learn something quickly and comprehensively, and I am able to immediately apply that newly learned skill to solve real problems. This is the beauty and value of the academic experience at Minerva. It’s not just about the subject matter, it’s about the skills, too.

I have been lucky enough to have been able to practice and apply these technical skills during several internships throughout my college experience, working in both large international companies and small startups. Most recently, I interned with Amazon at their European headquarters in Luxembourg. I worked in People Analytics and was part of an interdisciplinary Human Resources team that focused on addressing some of Amazon’s toughest organizational issues in a quantitative way.

During this internship, I was able to apply my skills in statistics and impact evaluation on a large scale to help solve problems that mattered. I was also able to quickly learn new technical skills, such as advanced Excel techniques and SQL. This allowed me to create meaningful data analysis and make legitimate, statistically-backed recommendations to my team based on my findings. The skills I learned in Minerva classes, such as Formal Analysis and Knowledge: Information Based Decisions, were incredibly helpful in finding and executing analytical techniques, and have shaped my thinking about problem-solving and decision making. Alongside analytical opportunities, I was given the chance to teach other interns and staff powerful statistical methodologies and technologies, which enabled them to make their own projects more data-centric.

Becoming a CS major didn’t mean that I have to abandon my interests in the arts and humanities. In fact, I’ve found that a data-centric focus compliments my other favorite subjects. This semester, I decided to combine my final projects for two of my classes: Modelling, Simulation, and Decision Making, and Constructing Theories of Good Governance. In this project, I used network theory to model the problem of gerrymandering (unfair district boundaries) in United States elections, analyzed different algorithms for redistricting, and made policy recommendations based on my simulations. It was an amazing project to work on, and being able to synthesize both of my classes has improved my understanding of each individually. My government essay was greatly enhanced by my quantitative analysis, and my modelling and simulation project was relevant and meaningful because it addressed a current and interesting problem. I believe that everything I do in the social sciences and humanities is enhanced by my knowledge of CS.

Studying CS at Minerva is preparing me for the postgraduate life in ways I never imagined before. I plan to enter the education technology sphere, and Minerva’s CS curriculum is uniquely preparing me for this career path. This summer, I will be attending the Wolfram Summer Program, specializing in education innovation. There, I will learn the Wolfram Language and create a product that will help students and teachers develop their quantitative skills. In the education technology sector, the boundaries between technology and pedagogy are constantly shifting and evolving. The skills I have learned at Minerva — such as being able to quickly learn new technologies and apply innovative thinking to problems — combined with my experiences in the community have prepared me to succeed in the ever-changing field of education.

Quick Facts

Name
Country
Class
Major

Social Sciences & Business

Business & Computational Sciences

Business and Social Sciences

Social Sciences and Business

Computational Sciences & Social Sciences

Computer Science & Arts and Humanities

Business and Computational Sciences

Business and Social Sciences

Natural Sciences

Arts and Humanities

Business, Social Sciences

Business & Arts and Humanities

Computational Sciences

Natural Sciences, Computer Science

Computational Sciences

Arts & Humanities

Computational Sciences, Social Sciences

Computational Sciences

Computational Sciences

Natural Sciences, Social Sciences

Social Sciences, Natural Sciences

Data Science, Statistics

Computational Sciences

Business

Computational Sciences, Data Science

Social Sciences

Natural Sciences

Business, Natural Sciences

Business, Social Sciences

Computational Sciences

Arts & Humanities, Social Sciences

Social Sciences

Computational Sciences, Natural Sciences

Natural Sciences

Computational Sciences, Social Sciences

Business, Social Sciences

Computational Sciences

Natural Sciences, Social Sciences

Social Sciences

Arts & Humanities, Social Sciences

Arts & Humanities, Social Science

Social Sciences, Business

Arts & Humanities

Computational Sciences, Social Science

Natural Sciences, Computer Science

Computational Science, Statistic Natural Sciences

Business & Social Sciences

Computational Science, Social Sciences

Social Sciences and Business

Business

Arts and Humanities

Computational Sciences

Social Sciences

Social Sciences and Computational Sciences

Social Sciences & Computational Sciences

Social Sciences & Arts and Humanities

Computational Science

Minor

Computational Science & Business

Economics

Social Sciences

Concentration

Applied Problem Solving & Computer Science and Artificial Intelligence

Computer Science and Artificial Intelligence & Cognition, Brain, and Behavior

Designing Societies & New Ventures

Strategic Finance & Data Science and Statistics

Brand Management and Designing Societies

Data Science & Economics

Machine Learning

Cells, Organisms, Data Science, Statistics

Arts & Literature and Historical Forces

Artificial Intelligence & Computer Science

Cells and Organisms, Mind and Emotion

Economics, Physics

Managing Operational Complexity and Strategic Finance

Global Development Studies and Brain, Cognition, and Behavior

Scalable Growth, Designing Societies

Business

Drug Discovery Research, Designing and Implementing Policies

Historical Forces, Cognition, Brain, and Behavior

Artificial Intelligence, Psychology

Designing Solutions, Data Science and Statistics

Data Science and Statistic, Theoretical Foundations of Natural Science

Strategic Finance, Politics, Government, and Society

Data Analysis, Cognition

Brand Management

Data Science and Statistics & Economics

Cognitive Science & Economics

Data Science and Statistics and Contemporary Knowledge Discovery

Internship
Higia Technologies
Project Development and Marketing Analyst Intern at VIVITA, a Mistletoe company
Business Development Intern, DoSomething.org
Business Analyst, Clean Energy Associates (CEA)

Conversation

I never imagined that I would study Computational Sciences (CS) in college. I grew up in the United Kingdom (UK) where students have to narrow down their academic focus very early on in high school, and I was distinctly a humanities student — I loved studying English literature, philosophy, ancient history, theatre, and creative writing. After taking a gap year in Norway, I studied education at a traditional university in the UK before deciding to transfer to Minerva, an institution I knew would challenge me in completely new ways.

Initially, I intended to major in Arts and Humanities, since I had an interest in both philosophy and psychology. But Minerva’s first-year curriculum, which teaches students how to think critically and creatively, inspired me to broaden my academic interests and challenge myself by pursuing CS.

In order to prepare for this shift in my studies, I had to learn a lot about the field of CS by myself. The summer before my first year at Minerva, I taught myself the programming languages Python and R, read books on computational thinking, sharpened my statistical knowledge, and relearned all the math I’d forgotten in the three years since I finished high school.

Once I arrived at Minerva, I met my amazing academic advisor, who saw my potential in CS and encouraged me to pursue analytical subjects. CS is taught very differently at Minerva compared to other university programs. My younger brother is currently in his first year of studying CS at a traditional university in the United Kingdom, and our experiences have been quite divergent. There are some advantages to his degree; he spends a lot of time in labs learning robotics and game design in a really fun way, and he is taught programming languages in detail, guided through each step from beginning to end.

As for me, the Minerva curriculum has prepared me to take on challenges, even those that I haven’t been explicitly taught. For example, I can find documentation for fragments of code to help find a solution, and I know how to use resources like Stack Overflow to get help from the coding community. My classmates and I learn a lot of the material by ourselves because most introductory information is easily accessible on the internet. Our classes focus on more advanced material and real-life application. In my second year, I explored topics like genetic matching and techniques to prove causation that many students at traditional schools will not be introduced to until graduate school.

Yes, academics at Minerva are hard — but the challenge has been worth it; one of the most valuable takeaways is the shift in the way I think. I’ve learned how to use a variety of resources to work through a problem. I’ve learned how to learn something quickly and comprehensively, and I am able to immediately apply that newly learned skill to solve real problems. This is the beauty and value of the academic experience at Minerva. It’s not just about the subject matter, it’s about the skills, too.

I have been lucky enough to have been able to practice and apply these technical skills during several internships throughout my college experience, working in both large international companies and small startups. Most recently, I interned with Amazon at their European headquarters in Luxembourg. I worked in People Analytics and was part of an interdisciplinary Human Resources team that focused on addressing some of Amazon’s toughest organizational issues in a quantitative way.

During this internship, I was able to apply my skills in statistics and impact evaluation on a large scale to help solve problems that mattered. I was also able to quickly learn new technical skills, such as advanced Excel techniques and SQL. This allowed me to create meaningful data analysis and make legitimate, statistically-backed recommendations to my team based on my findings. The skills I learned in Minerva classes, such as Formal Analysis and Knowledge: Information Based Decisions, were incredibly helpful in finding and executing analytical techniques, and have shaped my thinking about problem-solving and decision making. Alongside analytical opportunities, I was given the chance to teach other interns and staff powerful statistical methodologies and technologies, which enabled them to make their own projects more data-centric.

Becoming a CS major didn’t mean that I have to abandon my interests in the arts and humanities. In fact, I’ve found that a data-centric focus compliments my other favorite subjects. This semester, I decided to combine my final projects for two of my classes: Modelling, Simulation, and Decision Making, and Constructing Theories of Good Governance. In this project, I used network theory to model the problem of gerrymandering (unfair district boundaries) in United States elections, analyzed different algorithms for redistricting, and made policy recommendations based on my simulations. It was an amazing project to work on, and being able to synthesize both of my classes has improved my understanding of each individually. My government essay was greatly enhanced by my quantitative analysis, and my modelling and simulation project was relevant and meaningful because it addressed a current and interesting problem. I believe that everything I do in the social sciences and humanities is enhanced by my knowledge of CS.

Studying CS at Minerva is preparing me for the postgraduate life in ways I never imagined before. I plan to enter the education technology sphere, and Minerva’s CS curriculum is uniquely preparing me for this career path. This summer, I will be attending the Wolfram Summer Program, specializing in education innovation. There, I will learn the Wolfram Language and create a product that will help students and teachers develop their quantitative skills. In the education technology sector, the boundaries between technology and pedagogy are constantly shifting and evolving. The skills I have learned at Minerva — such as being able to quickly learn new technologies and apply innovative thinking to problems — combined with my experiences in the community have prepared me to succeed in the ever-changing field of education.