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, exploring, applying, and communicating mathematical concepts.
The curriculum is structured around these principles:
Algebra is foundational as a modeling and problem-solving tool
Geometry in two and three dimensions is integrated across topics at all levels and includes coordinate and transformational approaches
The study of vectors, matrices, counting, data analysis, and other topics from discrete mathematics is woven into core courses
Computer-based and calculator-based activities are part of core courses
Topics are explored visually, symbolically, and verbally
The capacity to develop problem-solving strategies depends on an accumulated body of knowledge
Statistics is the art and science of collecting, organizing, analyzing, and drawing conclusions from data. Course topics include exploring data, sampling and experimentation, probability and simulation, and statistical inference. Students use technology, investigations, problem-solving, and writing to build conceptual understanding. This course is recommended for those interested in any field that uses data, including the sciences, engineering, social sciences, and business studies.
This course involves foundational problem-solving skills, the translation of prose into mathematical equations and diagrams, oral and written presentations of mathematical processes, and mathematical intuition. Topics from algebra and geometry are integrated and include conversions and rates, proportional reasoning, area and perimeter, linear and quadratic equations, transformations of curves, inequalities, absolute values, and coordinate geometry. An emphasis on algebra skills supports problem solving.
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, vectors, circles, triangles, quadrilaterals 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.
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 course. Logarithms are used to straighten nonlinear data, and matrices are used to describe geometric transformations and various patterns of growth.
These courses build on the foundations of functions and trigonometry and provide an introduction to both integral and differential calculus. Calculus topics include, but not limited to, limits, first and second derivatives of the basic functions, applications to maxima and minima and rates of change, as well as integration techniques and applications to area and volume. Math 4i also includes topics from analysis (sequences and series, vectors, polar and parametric functions, and complex numbers) and discrete math (combinatorics and probability, and trigonometry (sum/difference formulas and trigonometric identities).
These courses are continuations of differential and integral calculus. Topics include, but not limited to: the theory of differential equations, complex analysis, sequences, series (including Taylor series and power series) and convergence tests, the theory of indeterminate forms, improper integrals, and applications.
This course starts with the tools, techniques, and concepts of linear algebra, emphasizing linear algebraic systems (together with matrix wizardry) to generalize toward underlying abstract structures: vector spaces, linear maps, and the fundamental theorem of linear algebra. Later topics include inner products and norms, orthogonality (including Gram-Schmidt factorization, Legendre polynomials), eigenvalues and singular values (including the spectral theorem, the Schur decomposition and Jordan canonical form) as well as applications such as minimization and least squares, data fitting and interpolation, Fourier series, iterations, and dynamics (systems of differential equations).
This course introduces students to the beauty and whimsy of abstraction without losing track of algebra’s practical roots. Using proofs, students learn how to generalize the basic rules of addition and multiplication to objects other than usual numbers and how those rules give structure to collections of objects. Topics include structures such as vector spaces, groups, rings, fields, and their applications to coding theory and public-key cryptography, symmetries, geometric constructions, and Galois theory.
computer science
The College Prep computer science program allows for beginning through advanced opportunities to study foundational computer science principles and concepts through the lens of Python, an ideal first programming language whose versatility makes it an excellent choice for a wide variety of applications. The introductory course (CS1) is a deep dive into programming, building a foundation in the general constructs of languages. In the 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) focuses on data science, analysis, and modeling.
This course demystifies how computers work, how data can be manipulated and moved around the world, and teaches proficiency in the Python programming language through hands-on labs and projects. The course introduces problem-solving strategies that help students debug, reflect upon, and improve their work. Students build and showcase their skills through pair programming, interactive modules, and a series of collaborative programming opportunities.
This course focuses on fundamental concepts of computer programming: abstraction, algorithms, efficiency, and data manipulation. 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, making 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.
This course equips students with the tools and skills of a data scientist. 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.
List of 8 members.
Kevin Wray
Math Teacher
510-652-0111 x 234
Francis Frederick
Math Teacher
510-652-0111 x234
Cliff Kao
Math Teacher
510-652-0111 x234
Minh Nguyen
Math Teacher
510-652-0111 x 234
Norm Prokup
Math /Computer Science Teacher
510-652-0111 x234
Margot Schou
Math Teacher
510-652-0111 x234
Cuong Ta
Math Teacher
510.652.0111 x234
Gretchen Verner
Math Teacher
510-652-0111 x234
I’ve wanted to be a math teacher since I was in high school. Math is sometimes thought to be a solemn subject, but I always look for unexpected moments that will captivate the students, or make them laugh. It resets the classroom and it is engaging for all of us.”