Computer Science: Algorithms, Theory, and Machines from Coursera

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. People who are interested in digging deeper into the content may wish to obtain the textbook Computer Science: An Interdisciplinary Approach (upon which the course is based) or to visit the website introcs.cs.princeton.edu for a wealth of additional material.

This course does not offer a certificate upon completion.

What's inside

Syllabus

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.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Demystifies computation, building awareness of substantial intellectual underpinnings and rich history of computer science

Emphasizes relationships between applications programming, theory of computation, real computers, and the field's history and evolution

Taught by Robert Sedgewick and Kevin Wayne, recognized researchers and educators in computer science

Provides insights into the fundamental design of computer processors, crucial for understanding how code gets its job done

Introduces classic algorithms and theoretical models, fostering a deep understanding of computer science principles

Requires no prior knowledge of computer science, making it accessible to beginners in the field

Reviews summary

Deep dive into cs fundamentals

According to learners, this is an outstanding course that provides a deep dive into fundamental computer science concepts. Students praise the coverage of algorithms, the limits of computation, and how computers actually work at a deep level. The course features excellent instructors and top-notch materials, with assignments described as challenging but rewarding. However, the course is also noted as challenging and having a fast pace, potentially feeling abstract in sections like machine architecture. It requires prerequisite knowledge in programming and logic, and the recommended textbook is seen as essential for full understanding.

Strong in theory, sometimes lacks practical ties.

"...the section on machine architecture felt very abstract and hard to follow without more practical examples or labs."

"The theory parts are interesting, but the section on machine architecture felt very abstract and hard to follow..."

"...the concepts were explained in a very theoretical way without enough practical application."

Companion textbook is highly useful.

"...though the recommended textbook is essential for fully grasping everything."

"The textbook is necessary, but adds cost."

Excellent lectures and course materials provided.

"The instructors are excellent, and the materials are top-notch, though the recommended textbook is essential..."

"Excellent lectures explaining complex topics clearly."

"The lectures are dense but full of valuable insights."

Covers core CS principles deeply.

"An absolutely outstanding course. Covers fundamental algorithms, the limits of computation, and how computers actually work at a deep level."

"This course is exactly what I was looking for - a deep dive into why computers work the way they do."

"Covers essential CS concepts often skipped in programming-focused tracks."

Assumes prior programming/logic knowledge.

"Assumes a stronger math/logic background than I had."

"It definitely requires the Programming with a Purpose prerequisite or similar background."

"Not for the faint of heart or those without a strong CS background already."

The course is demanding and fast-paced.

"The pace can be quite fast, especially in the later weeks covering circuits and CPU design. Some parts felt a bit rushed."

"Found this course very difficult. Assumes a stronger math/logic background than I had. The pace was relentless..."

"It's a challenging course, definitely not easy. Requires dedication and time."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computer Science: Algorithms, Theory, and Machines with these activities:

Review basic Java programming concepts

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Ensure a strong foundation by refreshing your knowledge of basic Java programming concepts.

Browse courses on Java Programming

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Review online tutorials or documentation.
Solve simple coding exercises.

Join a study group for combinatorial circuits

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Engage with other learners and solidify your understanding of combinatorial circuits through group discussions and problem-solving.

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Find or create a study group with peers.
Review course materials and prepare questions.
Meet regularly to discuss concepts and solve problems.

Read Introduction to the Theory of Computing

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Expand your knowledge by delving into the foundations of theoretical computer science with this classic textbook.

View Introduction to the Theory of Computation on Amazon

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Read a chapter and summarize the key concepts.
Solve the chapter's exercises.

Five other activities

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Practice binary search and mergesort

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Reinforce your understanding of classic algorithms by solving problems on platforms like LeetCode or HackerRank.

Browse courses on Sorting and Searching

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Choose a problem related to binary search or mergesort.
Implement the algorithm in your preferred programming language.
Test your implementation with various inputs.

Build a linked list from scratch

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Deepen your understanding of data structures by implementing a linked list from scratch in your preferred programming language.

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Design the node structure for your linked list.
Implement the basic operations (e.g., add, remove, search).
Test your implementation with various inputs.

Develop a presentation on von Neumann machines

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Demonstrate your understanding of computer architecture by creating a presentation that explains the principles of von Neumann machines.

Browse courses on Computer Architecture

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Research the topic and gather relevant information.
Create visual aids and organize your presentation.
Practice delivering your presentation.

Build a virtual machine simulator

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Develop a deeper understanding of processor design by building a simulator for a simple virtual machine.

Browse courses on Turing Machines

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Choose a tutorial or online resource.
Implement the basic components of the virtual machine.
Test your simulator with various programs.

Implement a small compiler

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Challenge yourself by building a fully functional compiler for a simple programming language.

Browse courses on Compilers

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Design the syntax and semantics of your language.
Implement the lexical analyzer and parser.
Generate intermediate code or assembly.

Career center

Learners who complete Computer Science: Algorithms, Theory, and Machines will develop knowledge and skills that may be useful to these careers:

Computer Architect

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Computer Scientist

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Machine Learning Engineer

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Artificial Intelligence Engineer

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Data Scientist

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Data Analyst

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Web Developer

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Computer Systems Analyst

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Database Administrator

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Systems Administrator

Systems Administrators maintain and operate computer systems and networks. This course may be useful for Systems Administrators because it provides a solid foundation in computer science principles, including algorithms, theory, and machines, which are essential for understanding and managing computer systems.

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Computer Programmer

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Software Engineer

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Software Developer

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