Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.
Math is everywhere. In this class, you’ll gain an in-depth understanding of algebraic principles, many of which you may have seen before, and learn how to use them to solve problems that we encounter in everyday life. The online version of College Algebra will cover all of the topics that you would see in more traditional class formats, but it will present the material in a way that we hope you’ll find fresh and interesting. You will learn about functions, polynomials, graphing, complex numbers, exponential and logarithmic equations, and much more, all through exploring real-world scenarios.
This course provides a brief review of introductory algebra topics. Topics to be covered include integer operations, order of operations, perimeter and area, fractions and decimals, scientific notation, ratios and rates, conversions, percents, algebraic expressions, linear equations, the Pythagorean theorem, and graphing.
Throughout this course, we will use algebra to quantify and describe the world around us. Have you ever wondered how many songs can fit onto your flash drive? By the end of the course, you’ll have stronger skills for modeling problems, analyzing patterns, and using algebra to arrive at conclusions.
Learn the concepts and methods of linear algebra, and how to use them to think about computational problems arising in computer science. Coursework includes building on the concepts to write small programs and run them on real data.
This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
This course provides a brisk, challenging, and dynamic treatment of differential and integral calculus, with an emphasis on conceptual understanding and applications to the engineering, physical, and social sciences.
This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. Part I covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.
In this course, you will learn how to formalize information and reason systematically to produce logical conclusions. We will also examine logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.