Precalculus I (saylor.org)

Offered by Saylor.org,
Precalculus I (saylor.org)

Precalculus I is designed to prepare you for Precalculus II, Calculus, Physics, and higher math and science courses. In this course, the main focus is on five types of functions: linear, polynomial, rational, exponential, and logarithmic. In accompaniment with these functions, you will learn how to solve equations and inequalities, graph, find domains and ranges, combine functions, and solve a multitude of real-world applications.

Precalculus I is designed to prepare you for Precalculus II, Calculus, Physics, and higher math and science courses. In this course, the main focus is on five types of functions: linear, polynomial, rational, exponential, and logarithmic. In accompaniment with these functions, you will learn how to solve equations and inequalities, graph, find domains and ranges, combine functions, and solve a multitude of real-world applications.

In this course, you will not only be learning new algebraic techniques that are necessary for other math and science courses, but you will be learning to become a critical thinker. You will be able to determine what is the best approach to take such as numerical, graphical, or algebraic to solve a problem given particular information. Then you will investigate and solve the problem, interpret the answer, and determine if it is reasonable.

A few examples of applications in this course are determining compound interest, growth of bacteria, decay of a radioactive substance, and the maximum height of a rocket. You will also use a graphing calculator to model a data set and find the function of best-fit and then interpolate or extrapolate from that function.

Upon successful completion of this course, you will be able to:

  • define the concept of function and determine the domain, range, inverse, and symmetries of functions;
  • graph linear, absolute value, root, piecewise, polynomial, rational, exponential, and logarithmic functions and circles;
  • identify the properties of polynomial and rational functions such as degree, maximum number of zeros, maximum number of turns, multiplicity of zeros, vertical asymptotes, horizontal asymptotes, and long-run behavior;
  • compute the equations of linear, polynomial, rational, exponential, and logarithmic functions analytically given appropriate data;
  • estimate solutions to and solve equations involving linear, absolute value, root, polynomial, rational, exponential, and logarithmic functions;
  • solve inequalities involving linear, absolute value, and polynomial functions;
  • utilize multiple approaches to describe functions such as verbally, algebraically, in tabular form, or graphically;
  • solve and analyze application problems such as optimization or growth/decay, using the appropriate functions, and evaluate the reasonableness of the solution; and
  • utilize technology to model linear, polynomial, exponential, and logarithmic data and interpret the results.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Computer Science II (saylor.org) Saylor Academy
Saylor.org

Introduction to Computer Science II (saylor.org)

This course is a continuation of the first-semester course titled CS101: Introduction to Computer Science I. It will introduce you to a number of more advanced Computer Science topics, laying a strong foundation for future academic study in the discipline. We will begin with a comparison between Java—the programming language utilized last semester—and C++, another popular, industry-standard programming language.

Self Paced
Self-Paced
Matrix Methods (Coursera) Coursera
University of Minnesota

Matrix Methods (Coursera)

Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction.

Nov 9th 2026
5-12 Weeks
Introduction to Statistics (saylor.org) Saylor Academy
Saylor.org

Introduction to Statistics (saylor.org)

The purpose of this course is to introduce you to the subject of statistics as a science of data. There is data abound in this information age; how to extract useful knowledge and gain a sound understanding in complex data sets has been more of a challenge. In this course, we will focus on the fundamentals of statistics, which may be broadly described as the techniques to collect, clarify, summarize, organize, analyze, and interpret numerical information.

Self Paced
Self-Paced
Real Analysis II (saylor.org) Saylor Academy
Saylor.org

Real Analysis II (saylor.org)

Real Analysis II is the sequel to Saylor’s Real Analysis I, and together these two courses constitute the foundations of real analysis in mathematics. In this course, you will build on key concepts presented in Real Analysis I, particularly the study of the real number system and real-valued functions defined on all or part (usually intervals) of the real number line.

Legacy Course
Self-Paced