数学和计算机科学

College Prep’s math program is problem based and student centered.

Using an approach that integrates the traditional areas of mathematics—algebra, geometry, trigonometry, pre-calculus, and calculus—throughout six sequential levels of study, students become independent learners who excel in reading, writing about, exploring, applying, and communicating mathematical concepts.

课程设置围绕这些原则展开。

代数作为建模和解决问题的工具，是基础性的。
二维和三维的几何学贯穿于各个层次的主题，包括坐标和变换的方法
在核心课程中贯穿了向量、矩阵、计数、数据分析等离散数学的学习内容。
以计算机为基础的活动和以计算器为基础的活动是核心课程的一部分。
以视觉、符号和口头方式探讨主题。
制定解决问题战略的能力取决于积累的知识体系。

These principles are addressed in the integrated curricula of Math 1-6. Math 3, 4, and 5 are each offered at two levels that showcase different teaching and learning styles.

The standard classes feature more direct teacher instruction and cover fewer topics. The “i” versions of each course cover more topics at a faster pace as students work more independently. Both levels require collaboration in the form of daily group work among four tablemates. The program also offers opportunities for advanced work, including AP Statistics, Math 5/5i, and Math 6. Math 5/5i prepares students for either the AP Calculus AB or BC exam while Math 6 covers multivariable calculus. Math Club, open to all interested students, meets regularly to share ideas and investigate problems beyond the scope of the normal curriculum and to help students prepare for local and national
math competitions.

分班测试是用来确定每个新生的数学水平。数学和科学学术支持专家、数学办公室的老师以及数学小队的同伴辅导员都会提供数学支持。

7个项目的清单。

数学1

This course includes topics from algebra, geometry, and trigonometry. Students learn techniques and theorems through problem solving. Collaborative study helps develop the ability to reflect on and explain mathematical processes. Topics include lines, polygons and vectors, circles and parabolas, and right triangle trigonometry. Similarity and congruence are studied through the lens of transformations. An investigation of linear motion leads to the use of parameters and consideration of optimal paths of travel.
数学2

本课程培养解决问题的基本技能，将散文转化为数学方程和图表，口头和书面介绍数学过程，以及数学直觉。代数和几何学的主题被整合在一起，包括换算和速率、比例推理、面积和周长、线性和二次方程、不等式和坐标几何。对代数技能的强调支持了问题的解决。
数学3和3i

These courses explore nonlinear motion and nonlinear functions: circular motion and the functions that describe it, ellipses and hyperbolas, exponential and logarithmic functions, dot products and matrices, and geometry on the surface of the earth. Advanced trigonometric techniques recur throughout the year. Logarithms are used to straighten nonlinear data, and matrices are used to describe geometric transformations and various patterns of growth.
数学4和4i

这些课程建立在函数和三角学的基础上，并继续进入微积分入门。分析主题包括序列和系列、向量、极值和参数函数以及复数。离散数学的主题包括组合学和概率。三角学的题目包括和/差公式和三角学特征。向量题目包括点积及其应用。微积分课题包括极限、基本函数的第一和第二导数、最大值和最小值的应用以及变化率。
数学5和5i

These courses are equivalent to differential and integral calculus at the college level. Math 5 covers techniques and applications of derivatives and integrals. It prepares students for the “AB” AP Calculus Exam. Math 5i covers the same material along with additional topics, such as infinite series, differential equations, and recursion. This course prepares students for the “BC” AP Calculus Exam.
数学6

这门多变量微积分课程将单变量微积分中介绍的微分和积分概念扩展到一个以上变量的函数中。主题包括参数曲线、极坐标、二维和三维的向量、偏导数、梯度、多变量的优化、线积分、多积分、格林、斯托克斯和高斯的定理（发散定理）。本课程还包括一阶微分方程、二阶常系数线性方程、傅立叶数列、拉普拉斯变换等内容。
AP统计学

统计学是收集、整理、分析数据并从数据中得出结论的艺术和科学。本课程主要关注四个主题：探索性数据分析、设计研究、概率模型和模拟以及统计推理。学生将设计、管理和统计调查和实验的结果。抽样分布为置信区间和假设检验提供了逻辑结构。学生使用TI-83/84图形计算器、JMP统计软件和基于网络的Java小程序来研究统计概念。本课程推荐给对任何使用数据的领域感兴趣的人，包括科学、工程、社会科学或商业研究。

College Prep offers Computer Science courses from beginning through advanced levels. The introductory course (CS1) is a deep dive into programming, developing proficiency in a single language (Python), and building a foundation in the general constructs of programming languages. In the department’s intermediate-level, project-based course (CS2), students apply their programming skills to build embedded system prototypes using microcontrollers—such as Arduinos and Raspberry Pis, sensors, and other electronics. The advanced course (CS3) focusses on data science, analysis, and modeling in Python.

4个项目的清单。

CS1：计算机科学基础

In this course students demystify how computers work, learn how data can be manipulated and moved around the world, and gain basic proficiency in a programming language. A variety of topics and skills are introduced through classroom discussions and hands-on labs and projects. The course uses Python as the primary language to gain a foundational framework of what programming is and how it works. Students showcase their skills through a series of collaborative and creative projects.
CS2：用Python进行计算机编程

Using the Python language, this course focuses on fundamental concepts of computer programming: abstraction, algorithms, efficiency, and data manipulation. Its simplicity and readability makes Python an ideal first programming language, and its versatility makes it an excellent choice for a wide variety of applications. Topics include the variables used in programming, Boolean logic and the use of conditional statements to control the flow of a program, and loops and how to apply recursion to solve problems. Students use functions to perform tasks that break a complex problem into smaller pieces that are easier to solve. The course introduces object-oriented programming in which students learn how to use objects and classes to provide a clear structure to their code that makes it easier to read, understand, and debug. Coding skills are honed on a series of individual and group projects. As a final project, students work in groups to design and create their own text adventure game.
CS3: Data Science

This course equips students with the tools and skills of a data scientist using the Python programming language. Students learn to collect and clean raw data, explore different data visualization tools that make it easier to see and understand trends, and learn to analyze their data, transforming and modeling it to draw conclusions and inform decision-making.
工程、电子、设计

This project-based course is for students interested in learning how to build things. The course focuses on mechatronics: the intersection of mechanical and electrical engineering and begins with the elements of design thinking. No design is perfect the first time; students learn from their mistakes and from observing the users of their designs. Students work on mini-projects that build in complexity throughout the semester. The goal of the early individual projects include building skills with the tools in the xLab, learning basic electronics, and programming Arduino micro-controllers. Many projects are centered on the Arduino—learning to tie together various input devices (e.g., switches, light sensors, temperature sensors, distance sensors, etc.) and output devices (e.g., motors, speakers, LEDs, LCDs, etc.). As students gain proficiency, projects become more open-ended and group-oriented and include regular design critiques.