ACADEMIC CURRICULUM
Below are the descriptions of typical academic courses offered by the Young Scholars Program. Courses are subject to change year-to-year, and the below courses may or may not be available.
MATHEMATICS COURSES
Game Theory: Strategy, Competition, and Cooperation*
How do animals compete for resources? Why do businesses make certain pricing decisions? How can we predict human behavior in strategic situations? In this course, we’ll explore the fascinating world of game theory—the mathematical study of strategy and decision-making. You’ll learn key concepts like the Nash equilibrium and evolutionary stable strategies. Through real-world examples from economics, biology, and everyday life, we’ll see how game theory helps explain competition, cooperation, and everything in between!
Students will be assessed based on participation in the classroom, quality and correctness of their written-up solutions and presentations, and quality and correctness of a group project. In-class discussions will be central to the course. Collaboration is strongly encouraged.
*One week of this course will be a boot camp in Problem Solving/Modeling
Exploring the Power of Linear Algebra: From Encryption to Dynamic Systems
Linear algebra is more than just matrices and vectors—it’s a fundamental tool that shapes the modern world. In this course, we uncover its surprising applications in cutting-edge fields. How does linear algebra safeguard digital security through encryption? What role does it play in Google’s search rankings and plagiarism detection? Beyond technology, we explore how it models complex systemic behaviors, from traffic flow and population dynamics to state-change problems. Through real-world examples and hands-on problem-solving, this class reveals the elegance and practicality of linear algebra in shaping both digital and physical systems.
Students will be assessed based on participation in the classroom, quality and correctness of their written-up solutions and presentations, and quality and correctness of a group project. In-class discussions will be central to the course. Collaboration is strongly encouraged.
BIOLOGICAL SCIENCES TRACT (each course 3 weeks)
Modern Molecular Biology Intensive
In this class, students will investigate the role of individual genes in cellular physiology using modern molecular tools. Students will learn about cloning, molecular biology, mammalian tissue culture, CRISPR gene editing homology-mediated repair, qPCR, fluorescent microscopy, and possibly next-generation sequencing. Instruction and practice in written and oral communication are also emphasized. The goal will provide an intensive exposure to a set of high-level lab skills to help students overcome initial hurdles often faced by those previously unexposed to a professional laboratory setting.
Fundamentals in Neuroscience
This course will teach basic principles of neuroscience using modern electrophysiological tools. Students will be taught to measure extracellular neural signals from invertebrate preparations using open-source electrophysiology hardware and will learn basic principles of data analysis including how to sort and count action potentials, the basic unit of communication between neurons. The goal is for students to establish a fundamental understanding the basis by which neurons communicate, and the basic principles of how neural activity is measured and analyzed.
PHYSICAL SCIENCES TRACT: (each course 3 weeks)
Intro to Quantum Computing & Information
We live in exciting times. The implications of quantum theory on the types of computers we can build and the ways we can communicate may be leading us to the cusp of a revolution. This course will introduce some of the key physics and mathematics behind the emerging field of quantum computing and quantum information. Note: Don't worry, you don't need to know quantum mechanics to take this course! We will teach you all the quantum mechanics you need to know and only assume a basic knowledge of linear algebra.
IDEA Lab: [I]nnovation, [D]esign & [E]ngineering in [A]ction
In this course, students will learn how to use Design Thinking and Engineering Technologies to solve real-world problems. Students will be guided through the process of identifying a problem, empathizing with stakeholders, ideating solutions, and developing a physical prototype of their invention. Students will learn 3D modeling and use 3D printers to fabricate solutions. Students will be encouraged to think critically, experiment, and iterate on their designs while learning the technical skills needed to innovate in an ever-changing world. Students will be assessed based on their participation in design discussions, the creativity and functionality of their prototypes, and their ability to communicate the design process and final product. Collaboration and teamwork are central to this course.
Computer Science with R
This course introduces basic topics of coding using the R programming language. The first three weeks will be devoted to learning the fundamentals of R programming, including hands-on practice assignments. Topics covered include introduction to RStudio interface, basic R coding syntax, data manipulation techniques, statistical analysis, and data visualization through graphing. The following two weeks will be project-based, where students will apply their R programming skills to analyze real ecological datasets to address current scientific questions about coral reef ecosystems. The final week will culminate in a final project submission. These projects will integrate the programming fundamentals covered in the first three weeks to implement data analysis, statistical testing, and create compelling visualizations of ecological data. Students will demonstrate their achievements after reaching each project milestone. The final project topic area will be determined by the student after consultation with the instructor and under the constraints of the material addressed in class.
Computer Science with Python
This course introduces topics in Computer Science using the Python programming language. The aim of the course is to learn how to use a computer language (Python) to facilitate your research. You will learn how to extract data, analyze data, and even simulate data. The first three weeks will be devoted to learning how to program with Python, including practice assignments. The following two weeks will be project-based in nature culminating with a final project submission in the last week of class. These projects will combine the basics covered in the first three weeks to implement computer science algorithms, data visualization, and digital humanities use cases. Students will demonstrate their achievements after reaching each project milestone. The final project topic area will be determined by the student after consultation with the instructor and under the constraints of the material addressed in class.