While students’ preferences are solicited and taken into account when making course assignments, the ultimate decision is up to the instructors. It is not first come, first served, and students may be placed in different courses than requested.
This course is intended to help students develop their problem solving skills using mathematics as a tool. The course will involve two main activities: (a) classroom meetings where students will investigate and discuss strategies for solving problems in mathematics, and formulate mathematical models for problems arising in the natural sciences; (b) computer laboratory activities where students will investigate problems and models using Excel and possibly Geogebra. Students will be assessed on the basis of their participation and performance during class meetings, the quality of their homework assignments, and 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. Please bring a USB flash drive for this course.
Examples of problems to be discussed:
- Model the evolution of an infection given a law for the spread of the infection.
- A power plant is to be located near three cities. Where should the plant be located such that the sum of the distances to the three cities is as small as possible?
- Given the birthrates, survival rates, and initial populations for each 10-year age group, determine the age distribution of the population in subsequent decades.
- Which numbers can be represented as the sum of two or more consecutive integers?
- Describe the polyhedra that can be constructed from faces that are pentagons and hexagons.
Topics from Calculus & Differential Equations
Instructor: Dr. Richard Oberlin, Assistant Professor of Mathematics
A mix of topics from differential equations and from the theoretical side of calculus. The course is designed for students who have already had a year of calculus.
From the theory of differential equations we will talk about:
- First order differential equations and their application to population laws, the spread of rumors, heating and cooling, and mixing;
- Second order linear differential equations including a thorough analysis of mechanical vibrations;
- Systems of differential equations including predator/prey problems, competing species, and epidemics.
From the theoretical side of calculus we will talk about:
- Properties of the real number system (why they, and not the rationals, are the numbers used in calculus);
- Rigorous definitions for various limits and for the concept of continuity;
- The proofs of some of the "big" theorems from Calculus I.
The Dynamic Organization of the Human Genome
Instructor: Dr. Jonathan Dennis, Associate Professor of Biological Science
In this course, we will use differentiation of stem cells as a model to explore examples of genome organization that broaden our fundamental understanding of gene regulation. We will work our way through the organization of the human genome, learn how genes are expressed, identify the potential of the genome in different cell types, identify epigenetic features of the genome, and map the structure of the genome. At every point in the course we will employ state of the art tools and techniques available at Florida State University (e.g. next generation sequencing). Critical thinking, interactive discussion, and hypothesis formulation will be emphasized. A strong desire for hands on experimentation is required.
Topics to be covered will include:
- the structure of DNA
- the structure and organization of genes
- the genetic code
- the signals involved in gene activity
- the interplay between genetics and epigenetics
- the composition and organization of the human genome
- the analysis of genomes using next generation sequencing
- the fundamentals of computational biology
Physics of the 20th and 21st Centuries
Instructors: Drs. Harrison Prosper & Mark Riley, Professors of Physics
Our emphasis will be on the physics of the 20th and 21st centuries, which is often called modern physics. Modern physics covers a wide range of topics that include statistical and quantum physics, relativity, nuclear and particle physics, astrophysics and cosmology. In this program, we shall explore through discussions, laboratory experiments and computation, several of these topics.
Topics to be covered will likely include:
- Particle Physics
- 3-D modeling
- Atoms, Molecules, Photons, Quantum Mechanics
- Nuclei, Radioactivity, Nuclear Spectroscopy
- Nuclei Fusion and Fission, Creation of the Elements
Scientific Computing with C++
Curriculum Coordinator: Dr. Gordon Erlebacher, Professor of Scientific Computing
This course will focus on instilling the core principles of computing into its students. Rather than approach the programming structure from a theoretical level, we will learn programming through an immersive and intuitive framework. Even from the very first day of class we will get our hands dirty, and after understanding the purpose behind our programs we will pull the curtains back and tackle the details involved in the examples. The C++ programming language will be used to explore the fundamentals behind computer science and in applying them to scientific programming. The primary objective in this course will be to learn the underlying principles involved in programming in an effort to understand how to learn on your own - learning new languages, new libraries, new algorithms, etc. We want you to see the big picture.
This will be a very dynamic course. We will have certain concepts to cover each lesson, and examples to help illustrate them - but from there we will just play with code! After all, we learn the best when we're having fun.
Computer Science with Python
Curriculum Coordinator: Dr. Xin Yuan, Professor of Computer Science
This course introduces advanced topics in Computer Science using the Python programming language. It is assumed that students have a basic understanding of computers and programming. The aim of the course is to introduce advanced topics using the Python programming language, such as data processing, graphical user interfaces, problem-solving with advanced algorithms, and writing programs to automatically access and analyze information from social networks (Facebook and/or Google and/or Twitter). The first three weeks will be devoted to learning how to program with Python, including practice assignments. The fourth week is devoted to data processing with file storage, followed by lectures and projects to learn and implement graphical user interfaces, advanced computer science algorithms, and online data analysis and principles of gaming. Each topic has a hands-on project the students can work on in class, in the laboratory, and off campus. Students will demonstrate their achievements after reaching each project milestone.