Applied Mathematics & Sciences2022-09-28T10:54:46+00:00

Applied Mathematics & Sciences

Placement Requirements

The placement process for new students is different from that for returning students. Please review the placement requirements for the appropriate group at the links below.

Science Placement Requirements

Placement Requirements for New Students
Placement Requirements for Returning Students

Mathematics Placement Requirements

Placement Requirements for Returning Students
Placement Requirements for New Students

All placements are subject to review by the head of the department.

Applied Mathematics & Sciences Courses

Computer Science

Available to all students

Engineering

Available to grades 11 & 12

Statistics & Personal Finance

Math 4 Semester Courses

Honors

Applied Mathematics & Sciences Course Descriptions

Introduction to Computer Science

Available to: all students

Schedule: one semester

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must concurrently be enrolled in a year of traditional science or have successfully completed three years of traditional science.

Introduction to Computer Science is designed for students with no assumed computer science background and requires no prior programming experience. In this introductory course, students develop problem-solving skills through the study of real-world examples, reflecting on various uses of technology in the worlds around them. We explore core topics such as design thinking, computational thinking, artificial intelligence, and basic programming syntax. Throughout the course, students will be introduced to a foundational toolbox in Scratch and then Python, a versatile and powerful programming language widely applicable across many fields.

Data Science

Available To: all qualified students, see placement requirement link above

Schedule: one semester

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must simultaneously be enrolled in a year of traditional science or have successfully completed three years of traditional science.

Data literacy is increasingly important in our world. This course combines the vital arenas of statistical knowledge and programming skills with the purpose of analyzing and visualizing the past, as well as predicting the future. The course content will address common applications in science, marketing, business, and sports, and will give students the skills and analytical tools necessary to learn from data efficiently and make informed decisions. The curriculum includes descriptive statistics, an overview of Python, Jupyter notebooks, an introduction to Pandas, data visualizations, exploratory data analysis, ethical issues, and predictive analytics. The prerequisite is Introduction to Computer Science or its equivalent.

Programming Methodology 

Available to: all qualified students, see placement requirement link above

Schedule: one semester

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must concurrently be enrolled in a year of traditional science or have successfully completed three years of traditional science.

Programming Methodology is a course designed for students who have a basic understanding of computer science and programming and want to further develop their programming skills. Through individual and group assignments, students will learn a number of important topics of basic programming such as types, numbers, strings, functions, linear collections, dictionaries, logic, decomposition, good programming style, whole-program structure, text, file-processing, debugging, and object oriented programming. Students will creatively and collaboratively learn important core features of the programming language that will help them solve real programming problems. To engage students and reinforce learning, students will perform short programming exercises during class as they learn new topics.

Data Structures & Algorithms / Honors

Available To: all qualified students, see placement requirement link above

Schedule: one semester

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must simultaneously be enrolled in a year of traditional science or have successfully completed three years of traditional science.

The subject of data structures and algorithms follows programming in a computer science curriculum, both at the college level as well as at high schools that offer advanced courses. It is a class that builds programming skills, but more importantly improves students’ ability to think logically, solve advanced problems (for example how your GPS finds the best route or how a video game “interacts” with the player), communicate, and be creative. The course curriculum includes algorithm analysis, linear structures, queues, recursion, sorting and searching algorithms, trees and tree algorithms, graphs and graph algorithms. The prerequisite is Programming Methodology or its equivalent, including object-oriented programming and writing and using classes in Python. The Honors version of the course includes a heavier workload and more stringent grading standards, and students in the course may choose to take the Computer Science A AP exam if they wish.

Engineering Design

Available to: qualified grade 11 and 12 students, see placement requirements link above

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must concurrently be enrolled in a year of traditional science or have successfully completed three years of traditional science.

This is a course that helps students understand the engineering design process, as well as how prototypes are used to give engineers the ability to explore design alternatives, test theories, and confirm performance. Students will be engaged in stimulating and collaborative hands-on problem-solving activities for the purpose of experiencing how engineers and technicians use a combination of mathematics, science, technology, and prototyping to discover solutions to problems they encounter. In addition to building on their creative and critical thinking skills as young engineers, students in this class will learn how to use Fusion 360 (3D computer aided design tool by Autodesk) as a digital design tool, along with 3D printers, to produce prototypes.

Mechatronics Engineering

Available To: qualified grade 11 and 12 students, see placement requirements link above

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must concurrently be enrolled in a year of traditional science or have successfully completed three years of traditional science.

Mechatronics is the union of electrical, mechanical, and computer engineering, and includes robotics. This course uses design and discovery surrounding mechatronics to expose students to various engineering disciplines and prepare them for introductory college-level engineering coursework, such as physical computing/coding with applied mathematics, control theory, and 3D modeling/printing. Students will engage in intriguing and challenging hands-on projects involving these topics to further develop important problem-solving and critical-thinking skills that are necessary to be an effective engineer. Projects include using an 8-LED display for sensor input and a game, designing an RGB lamp, programming an autonomous robot, and creating a wireless remote control car.

While no prior programming experience is required, it is helpful. Honors level projects will be available to challenge the more advanced student.

Personal Finance

This semester course gives students the opportunity to learn about essential elements of personal finance that they are likely to encounter as young adults both during and after college. Students learn about interest, the present and future value of money, debt, basic banking, investing, loans, retirement savings, insurance, and taxes. Throughout this course, students explore the nature of growth and decay, and compound interest. Overall, the course focuses on solving math problems related to financial literacy, providing students with the basic knowledge and tools they will need to apply their problem-solving abilities to their financial life. Throughout the course, students will engage in budgeting and stock investing simulations using an online application called Personal Finance Lab.

Statistics

This introductory statistics course will introduce students to the major concepts and tools for collecting, analyzing and drawing conclusions from data, as well as provide them with opportunities to apply what they have learned to real data sets. Students will develop statistical strategies from a wide variety of sources including experiments, sample surveys and other observational studies. Students will study probability and simulation to aid in their understanding of statistics and to aid in constructing models of chance. Also, students will study the properties of sampling distributions in order to construct confidence intervals and carry out hypothesis tests. Throughout the course, students will use technological tools such as graphing calculators, and spreadsheets to organize, display and analyze data.This course helps prepare students for an introductory course in statistics at the college level, and helps them become discerning consumers of data.

Statistics Honors

Type: honors

Available to: qualified students, see placement requirements link above

Statistics is a growing field of study that has applications in many industries and academic fields such as psychology, life sciences, economics, astronomy, finance, sports and more. Paying close attention to local, national and global events, this honors course introduces students to the descriptive and inferential statistical methods that allow them to be competent consumers and handlers of data. Throughout the year students will explore several statistical themes such as producing data with experimental design, exploring data with descriptive statistics, anticipating patterns using probability, and learning about a population from sample data using statistical inference. Students will engage with these concepts through activities, simulations, projects. current events, and real-world data sets. Also, they will develop familiarity with technological tools that will help them access, display, analyze and interpret data. Deep engagement in the coursework will help students to further develop their problem-solving, critical thinking, and communication skills, as well as prepare them for further studies and applications of statistics at the university level.

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