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
Mathematical Models: Theory and Practice
COURSE DESCRIPTION: The course will focus on modeling real-life situations, such as:
- What is the chance that a war will begin between two countries?
- How quickly does a disease spread across a population?
- How quickly does an advantageous gene spread?
The course will involve classroom meetings where we will discuss the theoretical side of the situation, and set up equations that model it. Students will do computer laboratory activities to investigate problems and models using Excel.
Students will be assessed on the basis of their participation and performance during class meetings, the quality of their homework assignments, and the correctness and exposition on a group project. This course provides practical, interactive experiences in using mathematics for solving a diverse range of problems. Collaborative work will be encouraged throughout the course
Pre-requisites: Calc AB/BC or equivalent
Nonlinear Thinking–- Our world is not intuitive!
COURSE DESCRIPTION: This course is an exploration of nonlinear phenomenon in the real world. We seek to think about what nonlinear implies about the nature of the world. This course will provide a framework to understand unintuitive, real phenomena in the world, such as:
- What are the implications of gravitational force being a linear force?
- How is a uniform density on a circle different from a uniform density on a line?
- How many people need to be at a party to ensure there is a 50% chance that some two people have the same birthday?
This course will involve classroom meetings where we develop theory underlying nonlinear phenomena and discuss how they are expressed in the language of mathematics. Students will periodically do presentations where they discuss nonlinear phenomena they perceive in the world. We will also use computer software (Excel, MATLAB) to visualize these effects.
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.
Pre-requisites: Algebra, Geometry, Pre-Calc or equivalent
In this class, students engage in independent research projects by using classic approaches with modern tools to investigate the role of individual genes in cellular physiology. Students will learn 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.
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.
This course introduces basic topics in Computer Science using the Python programming language. 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 on 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.
This course introduces advanced topics in Computer Science using the Python programming language such as data processing, graphical user interfaces, problem-solving with advanced algorithms, and writing programs utilizing Python packages. It is assumed that students have a basic understanding of computers and python programming. 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. A good portion of the course will be devoted to writing computational algorithms needed for various analysis of data.