This course introduces the broader discipline of computer science to people having basic familiarity with Java programming. It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). Our intent is to demystify computation and to build awareness about the substantial intellectual underpinnings and rich history of the field of computer science.
First, we introduce classic algorithms along with scientific techniques for evaluating performance, in the context of modern applications. Next, we introduce classic theoretical models that allow us to address fundamental questions about computation, such as computability, universality, and intractability. We conclude with machine architecture (including machine-language programming and its relationship to coding in Java) and logic design (including a full CPU design built from the ground up).
The course emphasizes the relationships between applications programming, the theory of computation, real computers, and the field's history and evolution, including the nature of the contributions of Boole, Shannon, Turing, von Neumann, and others.
All the features of this course are available for free. No certificate will be offered upon completion.
Computer Science: Algorithms, Theory, and Machines
4.8
(107 ratings)
20,981 already enrolled!
Offered By
Princeton University
Syllabus - What you will learn from this course
Week
110 minutes to complete
INFORMATION ABOUT LECTURES 1-10
This lesson provides information about the course Computer Science: Programming with a Purpose, which is the precursor to Computer Science: Algorithms, Theory, and Machines.
1 reading
1 reading
Information about Lectures 1-1010m
2 hours to complete
SORTING AND SEARCHING
We introduce and study classic algorithms for two fundamental problems, in the context of realistic applications. Our message is that efficient algorithms (binary search and mergesort, in this case) are a key ingredient in addressing computational problems with scalable solutions that can handle huge instances, and that the scientific method is essential in evaluating the effectiveness of such solutions.
5 videos (Total 71 min), 3 readings, 1 quiz
5 videos
Binary search10m
Insertion sort11m
Mergesort12m
Longest repeated substring19m
3 readings
Getting Started10m
Supplements for Lecture 1110m
Optional Enrichment on Sorting and Searching10m
1 practice exercise
Sorting and Searching8m
Week
22 hours to complete
STACKS AND QUEUES
Our introduction to data structures is a careful look at the fundamental stack and queue abstractions, including performance specifications. Then we introduce the concept of linked structures and focus on their utility in developing simple, safe, clear, and efficient implementations of stacks and queues.
5 videos (Total 69 min), 2 readings, 1 quiz
2 readings
Supplements for Lecture 1210m
Optional Enrichment on Stacks and Queues10m
1 practice exercise
Stacks and Queues8m
Week
31 hour to complete
SYMBOL TABLES
The symbol table abstraction is one of the most important and useful programmer's tools, s we illustrate with several examples in this lecture. Extending the scientific approach of the previous two lectures, we introduce and study binary search trees, a classic data structure that supports efficient implementations of this abstraction.
5 videos (Total 57 min), 2 readings, 1 quiz
2 readings
Supplements for Lecture 1310m
Optional Enrichment on Symbol Tables10m
1 practice exercise
Symbol Tables8m
Week
42 hours to complete
INTRODUCTION TO THE THEORY OF COMPUTING
The theory of computing helps us address fundamental questions about the nature of computation while at the same time helping us better understand the ways in which we interact with the computer. In this lecture, we introduce formal languages and abstract machines, focusing on simple models that are actually widely useful in practical applications.
5 videos (Total 63 min), 2 readings, 1 quiz
2 readings
Supplements for Lecture 1410m
Optional Enrichment on Theory of Computing10m
1 practice exercise
Theory of Computing8m
4.8
19 ReviewsTop Reviews
Loved this course! Such a great introduction to Computer Science. The course is really well broken down and the videos are very well done!
Excellent clarity and pace with real-life problems and challenges to really understand the concepts and their motivation.
Instructors
Robert Sedgewick
William O. Baker *39 Professor of Computer ScienceComputer Science
Kevin Wayne
Phillip Y. Goldman '86 Senior LecturerComputer Science
About Princeton University
Princeton University is a private research university located in Princeton, New Jersey, United States. It is one of the eight universities of the Ivy League, and one of the nine Colonial Colleges founded before the American Revolution.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
Can I earn a certificate in this course?
No. As per Princeton University policy, no certificates, credentials, or reports are awarded in connection with this course.
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