Course Designer: Dr. Bhanu Kapoor
After familiarizing yourself with the following course syllabus, log in or sign up and click the “Enroll me in this course” button near the top of the page. Once enrolled, navigate to Unit 1 of the course to read the Unit Introduction and Unit 1 Learning Outcomes. Links and instructions for all unit specific course resources will follow the introductory materials.
Earning College Credit
This course provides students the opportunity to earn actual college credit. It has been reviewed by Brandman University and can applied as credit towards a degree by students who are currently enrolled or plan to enroll at Brandman. You can read more about this special program here.
Evaluation and Minimum Passing Scores
In order to pass this course, you will need to earn a 70% or higher on the final exam. Your score on the exam will be tabulated as soon as you complete it. If you do not pass the exam on your first attempt, you may take it again as many times as needed, following a 7-day waiting period between each attempt.
You will only receive an official grade on your final exam. However, in order to adequately prepare for this exam, we recommend that you work through the materials in each unit. Throughout the course you may find practice quizzes or other assignments that will help you master material and gauge your learning. Scores on these assignments are informational only and do not contribute to your overall course grade.
If you are seeking to earn college credit at Brandman, you must take and pass the version of the exam titled "Proctored Final Exam." That exam will be password protected.
This course is delivered fully online. You will be required to have access to a computer or web-capable mobile device and have consistent access to the internet to either view or download the necessary course resources and to attempt any auto-graded course assessments and the final exam.
To access the full course including assessments and the final exam, you will need to be logged into your Saylor Academy account and enrolled in the course. If you do not already have an account, you may create one, free of charge, here. Although you can access some course resources without being logged into your account, it’s advised that you log in to maximize your course experience. For example, some of the accessibility and progress tracking features are only available when you are logged in.
There is no cost to access and enroll in this course. All required course resources linked throughout the course, including textbooks, videos, webpages, activities, etc are accessible for no charge. This course also contains a free final exam and course completion certificate.
This courses does contain an optional final exam that will provide students an opportunity to earn college credit. Access to the exam itself is free, though it does require the use of a proctoring service for identity verification purposes. The cost for proctoring is $25 per session.
While learning styles can vary considerably and any particular student will take more or less time to learn or read, we estimate that the "average" student will take 100 hours to complete this course. Each resource and activity within the course is similarly tagged with an estimated time advisory. We recommend that you work through the course at a pace that is comfortable for you and allows you to make regular (daily, or at least weekly) progress. It's a good idea to also schedule your study time in advance and try as best as you can to stick to that schedule.
It may be useful to take a look at these time advisories, to determine how much time you have over the next few weeks to complete each unit, and then to set goals for yourself. Perhaps you can sit down with your calendar and decide to complete Subunits 1.1 through 1.3 (a total of 3 hours) on Monday; Subunit 1.4 (a total of 2.5 hours) on Tuesday; Subunits 2.1 and 2.2 (a total of 2.5 hours) on Wednesday; etc.
Learning new material can be challenging, so below we've compiled a few suggested study strategies to help you succeed.
Take notes on the various terms, practices, and theories as you read. This can help you differentiate and contextualize concepts and later provide you with a refresher as you study.
As you progress through the materials, take time to test yourself on what you have retained and how well you understand the concepts. The process of reflection is important for creating a memory of the materials you learn; it will increase the probability that you ultimately retain the information.
Pay special attention to Unit 1, as it will lay the groundwork for understanding the more advanced, exploratory material presented in the latter units.
- explain and identify the importance of algorithms in modern computing systems and their place as a technology in the computing industry;
- indentify algorithms as a pseudo-code to solve some common problems;
- describe asymptotic notations for bounding algorithm running times from above and below;
- explain methods for solving recurrences useful in describing running times of recursive algorithms;
- explain the use of Master Theorem in describing running times of recursive algorithms;
- describe the divide-and-conquer recursive technique for solving a class of problems;
- describe sorting algorithms and their runtime complexity analysis;
- describe the dynamic programming technique for solving a class of problems;
- describe greedy algorithms and their applications;
- describe concepts in graph theory, graph-based algorithms, and their analysis;
- describe tree-based algorithms and their analysis; and
- explain the classification of difficult computer science problems as belonging to P, NP, and NP-hard classes.
Throughout this course, you'll also see related learning outcomes identified in each unit. You can use the learning outcomes to help organize your learning and gauge your progress.
- have read the Saylor Student Handbook;
- be knowledgeable about basics of computer programming using a high-level language, such as C/C++ and/or have completed CS101: Introduction to Computer Science I, CS102: Introduction to Computer Science II, CS201: Elementary Data Structure, and CS202: Discrete Structures from our Computer Science discipline;
- be comfortable in writing, compiling, and executing your own programs.
- be knowledgeable about basics of discrete mathematics concepts.