Discrete Mathematics and Probability Theory
Spring 2015

Instructor and Lecture

Course Syllabus

See syllabus below.


Key Information


Homework parties

Times: Friday 2:00-5:00pm in the Wozniak Lounge (430 Soda Hall)

Every week in the Wozniak Lounge, there will be a "homework party." This is completely optional. GSIs will be present in shifts as will some readers. Students are expected to help each other out, and if desired, form ad-hoc "pickup" homework groups in the style of a pickup basketball game.

The Woz is a relatively big space and if the weather is nice, we can also access the patio outside. But if the room is crowded, excercise good judgement and make room for others by leaving if you can find an alternative source of assistance. When the room is not crowded, people from the class are welcome to just hang out as long as they aren't bothering other people. Some social games might be available.

Homework assignments

Online homework



There is no textbook for this class. Instead, there is a set of fairly comprehensive lecture notes. The notes are undergoing a major revision this semester, so notes posted well in advance of lecture may change closer to the date. So make sure you revisit the notes after lecture. Note 0 is background material that you should make sure you understand before the first lecture. Each note may be covered in one or more lectures.

Discussion Sections

Click here for a list of the GSIs and their discussion sections.

You are free to choose which discussion section you want to attend. All sections will cover the same basic material, but different GSIs might have different approaches to it.

Discussion handouts

Weekly schedule

Weekly schedule

Schedule of Lectures





Final: May 15, 11:30-2:30


Discrete mathematics and probability theory provide the foundation for many algorithms, concepts, and techniques in the field of Electrical Engineering and Computer Sciences. For example, computer hardware is based on Boolean logic. Induction is closely tied to recursion and is widely used, along with other proof techniques, in theoretical arguments that are critical to understanding the foundations of many things, ranging from algorithms to control, learning, signal processing, communication, and artificial intelligence. Similarly for modular arithmetic and probability theory. CS70 will introduce you to these and other mathematical concepts. By the end of the semester, you should have a firm grasp of the theoretical basis of these concepts and their applications to general mathematical problems. In addition, you will learn how they apply to specific, important problems in the field of EECS.

This course is divided into two main units, each of which will introduce you to a particular mathematical concept as well as its applications. The units are:

1. Proofs and Discrete Structures



Modular Arithmetic

Diagonalization and Self-Reference

2. Probability Theory

Counting and Discrete Probability

Continuous Probability