OpenCourser brand icon
Sign in
We may earn an affiliate commission when you visit our partners.

Intro to Theoretical Computer Science

Sebastian Wernicke, Sean Bennett, and Sarah Norell

Sign up for Udacity's free Introduction to Theoretical Computer Science course and learn the basics in theoretical computer science and what they imply for solving algorithmic problems.

Enroll now

Here's a deal for you

We found an offer that may be relevant to this course.
Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Use code at checkout. Valid for a limited time only
Bootcamp level quality
Complete hands-on projects and get personalized feedback with Udacity.
Take
40%
off
UDACITY40

What's inside

Syllabus

Lesson 1.1 - Challenging Problems
Lesson 1.2 - Algorithm Analysis and the RAM
Lesson 1.3 - Big O (Optional)
Lesson 1.4 - Connecting Similar Problems
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Introduces theoretical computer science and its applications in algorithm problem-solving
Covers fundamental concepts like algorithm analysis, complexity, and NP-completeness
Taught by experienced instructors from Udacity
Provides a solid foundation for further studies in computer science
Requires basic programming knowledge and mathematical maturity
May require additional resources for deeper understanding of the concepts

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Intro to theoretical computer science review

According to students, this course serves as a valuable introduction to the core concepts of theoretical computer science. Learners appreciate that the course covers foundational topics like algorithmic analysis, NP-completeness, and undecidability. However, students frequently note that the subject matter itself is inherently complex and can be difficult to grasp, often requiring significant effort and perhaps a strong prior background in mathematics or related CS areas. The course is perceived as being very theory-heavy, which is expected for the topic, but some learners looking for practical application might find it less suitable. The problem sets are often described as demanding, pushing students to apply the theoretical concepts. Overall, it's seen as a solid, albeit challenging, stepping stone into the theoretical side of computing.
Focuses heavily on theory over practical application.
"Don't expect to build anything; you'll be working with concepts and proofs."
"As expected, this course is extremely theoretical with almost no coding or practical examples."
"If you're looking for hands-on programming or practical skills, this isn't the course for you."
"It's abstract theory from start to finish, which is great if that's what you want, but be aware."
Provides a solid base for advanced topics.
"This course gave me an excellent foundation in theory that helped significantly in later CS classes."
"I now have a much better understanding of algorithmic complexity and the limits of computation after taking this."
"It's a crucial starting point for anyone serious about understanding computer science fundamentals."
"The overview of NP-complete problems is invaluable for appreciating algorithmic hard limits."
May require prior math or CS knowledge.
"I felt a bit lost in some sections because I didn't have a strong discrete math background."
"While it's an intro, having some prior exposure to algorithms or proofs is definitely helpful."
"Might be tough if this is your absolute first dive into formal CS concepts."
"A bit of mathematical maturity goes a long way in this course."
Problem sets require significant effort and understanding.
"The problem sets were quite difficult and often took me a long time to complete, requiring revisiting lectures."
"You really need to struggle with the problem sets to internalize the concepts; they are not easy."
"Some problem set questions felt significantly harder than the examples shown in the lectures."
"Be ready to spend serious time on the homework; it's where the real learning happens (and struggle)."
Core theoretical concepts can be difficult to grasp.
"The material, especially NP-completeness and undecidability, was quite challenging to wrap my head around."
"I found some of the proofs and abstract ideas presented in the lectures hard to follow at times."
"This course requires you to really think deeply about computation limits, which isn't easy."
"Be prepared for dense concepts; this isn't a light introductory topic."

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 Intro to Theoretical Computer Science with these activities:
Read Introduction to Algorithms
Provide context for algorithmic analysis and its implications.
Show steps
  • Read chapters 1-3
  • Work through practice problems
Review basic probability and counting techniques
Refresh foundational skills in probability and combinatorics for better understanding of complexity analysis.
Browse courses on Probability
Show steps
  • Review textbooks or online resources
  • Solve practice problems and review concepts
Watch Big O Notation and Complexity Analysis tutorials
Deepen understanding of how to analyze algorithm efficiency.
Browse courses on Big O Notation
Show steps
  • Search for tutorials on YouTube or Coursera
  • Watch the tutorials and take notes
  • Try applying the concepts to practice problems
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Read Introduction to Algorithms
Build a stronger understanding of fundamental algorithms using a classic recommended text.
Show steps
  • Read the first six chapters of the book.
  • Complete the exercises at the end of each chapter.
  • Attend a book club discussion on the book.
Watch Algorithm Visualizations
Enhance your understanding of algorithms by visualizing their execution.
Browse courses on Algorithms
Show steps
  • Find an algorithm visualization tool or website.
  • Choose an algorithm that you are interested in.
  • Watch the visualization of the algorithm.
Solve LeetCode Problems
Reinforce your understanding of algorithms and data structures through regular practice.
Browse courses on Algorithms
Show steps
  • Choose a LeetCode problem that is related to the course material.
  • Solve the problem on your own.
  • Review your solution and compare it to the optimal solution.
Attend a study group for SAT problems
Foster collaboration and improve problem-solving skills for SAT problems.
Browse courses on SAT
Show steps
  • Find or join a study group
  • Work together to solve SAT problems
  • Share strategies and insights
Join a Study Group
Collaborate with peers to reinforce concepts and gain different perspectives on course material.
Browse courses on Collaboration
Show steps
  • Find a study group or create your own.
  • Meet regularly to discuss course material.
  • Work together on problem sets and projects.
Solve Leetcode problems
Reinforce algorithmic problem solving and coding skills.
Browse courses on Algorithms
Show steps
  • Choose problems tagged with algorithms and data structures
  • Break down the problem and design a solution
  • Implement the solution and test it with sample inputs
  • Analyze the time and space complexity of the solution
Develop a visual aid for NP-Completeness
Solidify understanding of NP-Completeness and its implications.
Browse courses on NP-Completeness
Show steps
  • Research NP-Completeness and its properties
  • Choose a visual representation (e.g., flowchart, mind map, infographic)
  • Create the visual aid, clearly illustrating the concept
Attend a workshop on Randomization in Algorithms
Gain practical experience and insights into the role of randomization in algorithm design.
Browse courses on Randomization
Show steps
  • Find and register for an appropriate workshop
  • Attend the workshop and participate actively
  • Apply the learned techniques to personal projects or assignments
Mentor a junior student in theoretical computer science
Reinforce understanding of concepts by explaining them to others, and develop leadership skills.
Browse courses on Mentoring
Show steps
  • Identify a junior student seeking guidance
  • Meet regularly to discuss concepts, provide support, and answer questions
  • Encourage the student to participate in relevant activities and competitions
  • Provide feedback and guidance on their progress

Career center

Learners who complete Intro to Theoretical Computer Science will develop knowledge and skills that may be useful to these careers:
Professor
A Professor is primarily focused on teaching a subject and researching in its subfield. They are often responsible for advising students, mentoring researchers, and publishing journal articles in their field. An understanding of theoretical computer science can guide a Professor in their approach to teaching.
See salaries and explore the career path for Professor
Data Scientist
Typically, a Data Scientist will be responsible for using coding and programming skills to gather, clean, and analyze data for various purposes. They often write and publish reports on the results of their analysis in their field, an area where a background in theoretical computer science will be valuable.
See salaries and explore the career path for Data Scientist
Software Engineer
A Software Engineer is responsible for the design, development, deployment, and maintenance of software systems. Mastery of theoretical computer science can help a Software Engineer better understand design principles and algorithms, improving their problem-solving skills.
See salaries and explore the career path for Software Engineer
Computer Programmer
Computer Programmers write and test code that allows software applications and computer programs to run. Their role is focused on the coding process itself, and the knowledge gained from theoretical computer science can enhance the skills of a programmer.
See salaries and explore the career path for Computer Programmer
Systems Analyst
A Systems Analyst examines an organization's current processes and procedures, and then designs and implements a better system. They will recommend hardware and software solutions to management while ensuring that a system meets an organization's needs. Knowledge of theoretical computer science can help equip a Systems Analyst to assess processes and design a system.
See salaries and explore the career path for Systems Analyst
Web Developer
Web Developers design and develop websites and web applications, often dealing with coding, scripting, content management, and visual design. Knowledge of theoretical computer science can help a Web Developer create more impactful and efficient web applications.
See salaries and explore the career path for Web Developer
Computer Systems Analyst
A Computer Systems Analyst studies and evaluates the computer systems and procedures within an organization. Their duty is to help improve the system by examining how users interact with it and designing or recommending changes. Understanding theoretical computer science can help a Systems Analyst create a more advanced and efficient system.
See salaries and explore the career path for Computer Systems Analyst
Database Administrator
A Database Administrator is responsible for the installation, configuration, maintenance, and performance monitoring of database management systems. Mastery of theoretical computer science can help a Database Administrator in designing, implementing, and maintaining a variety of different databases in a manner consistent with how the computer system operates.
See salaries and explore the career path for Database Administrator
Information Security Analyst
An Information Security Analyst's primary duty is to protect an organization's computer networks and systems from unauthorized access, use, disclosure, disruption, modification, or destruction. A background in theoretical computer science can provide an Information Security Analyst with a strong understanding of the methods used by malicious actors to compromise systems.
See salaries and explore the career path for Information Security Analyst
Network Administrator
A Network Administrator is responsible for managing and maintaining an organization's computer network. Their duty is to set up, maintain, and troubleshoot networks. Understanding theoretical computer science can help a Network Administrator have a strong foundation in the technology they deal with.
See salaries and explore the career path for Network Administrator
Computer and Information Systems Manager
A Computer and Information Systems Manager is responsible for planning, coordinating, and directing computer-related activities within an organization. They provide technical expertise and leadership to ensure that computer systems and information technology are used effectively and efficiently. Understanding theoretical computer science can help advance one's leadership in this role.
See salaries and explore the career path for Computer and Information Systems Manager
Operations Research Analyst
An Operations Research Analyst develops and applies analytical methods to help organizations make better decisions. They use mathematical and statistical models to analyze complex problems and recommend solutions. Understanding theoretical computer science can give an Operations Research Analyst tools to solve complex problems better.
See salaries and explore the career path for Operations Research Analyst
Computer Hardware Engineer
A Computer Hardware Engineer designs, develops, and tests computer hardware components. Their duty is to develop new hardware for computers and electronic devices. Understanding theoretical computer science can be useful for a Computer Hardware Engineer to design efficient hardware.
See salaries and explore the career path for Computer Hardware Engineer
Computer Scientist
Computer Scientists conduct research in various areas of computer science. Their duty is to advance the theory and practice of computing, developing new computing technologies and solving computational problems. A background in theoretical computer science is an important foundation for one in this role.
See salaries and explore the career path for Computer Scientist
Computer Science Teacher
A Computer Science Teacher educates students in computer science and programming. Their job is to design and deliver lesson plans, grade assignments, and provide support to students. An understanding of theoretical computer science can help a Computer Science Teacher provide a more robust education.
See salaries and explore the career path for Computer Science Teacher

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Intro to Theoretical Computer Science.
Cover image
Introduction to Algorithms, fourth edition
Save
This classic textbook covers a wide range of topics in theoretical computer science, including algorithms, data structures, and complexity theory. It valuable resource for students and professionals alike.
Introduction to Algorithms, fourth edition
Hardcover
$$$$
Introduction to Algorithms, fourth edition
Kindle Edition
$$$
Cover image
The Elements of Computing Systems, second edition
Save
Provides a comprehensive introduction to computer systems, from the hardware to the software. It great resource for students who want to learn more about the foundations of computer science.
The Elements of Computing Systems, second edition:...
Paperback
$$
The Elements of Computing Systems, second edition:...
Kindle Edition
$$
Cover image
Engineering Embedded Systems
Save
This textbook provides a broad overview of theoretical computer science, including topics such as automata theory, formal languages, and computability theory. It good resource for students who want to learn more about the theoretical foundations of computer science.
Engineering Embedded Systems: Physics, Programs,...
Kindle Edition
$$$
Cover image
Descriptive Complexity
Save
Provides a comprehensive introduction to computability theory and complexity theory. It good resource for students who want to learn more about the limits of computation.
Descriptive Complexity (Texts in Computer Science)
Paperback
$$$
Cover image
The Algorithm Design Manual
Save
Practical guide to algorithm design, with a focus on solving real-world problems. It provides a wealth of examples and exercises, making it a valuable resource for students and practitioners alike.
The Algorithm Design Manual (Texts in Computer...
Hardcover
$$$
The Algorithm Design Manual
Paperback
$$$
The Algorithm Design Manual (Texts in Computer...
Kindle Edition
$$
The Algorithm Design Manual
Kindle Edition
$$$
Cover image
Data Structures and Algorithms in Java
Save
This textbook provides a comprehensive introduction to algorithms and data structures. It good resource for students who want to learn more about the design and analysis of algorithms.
Data Structures and Algorithms in Java
Paperback
$$$$
Data Structures and Algorithms in Java, 6th Edition
Kindle Edition
$$$
Cover image
Discrete Mathematics and Its Applications
Save
This textbook provides a comprehensive introduction to discrete mathematics, which fundamental subject in computer science. It good resource for students who want to learn more about the mathematical foundations of computer science.
Discrete Mathematics and Its Applications
Paperback
$$$
Discrete Mathematics and Its Applications
Hardcover
$$$$
Student's Solutions Guide for Discrete Mathematics...
Paperback
$$$$
Connect Access Card for Discrete Mathematics and...
Printed Access Code
$$
Cover image
Introduction to Automata Theory, Languages, and...
Save
This textbook provides a comprehensive introduction to logic and automata theory. It good resource for students who want to learn more about the theoretical foundations of computer science.
Introduction to Automata Theory, Languages, And...
Hardcover
$$$$
Introduction to Automata, Theory, Languages and...
Hardcover
$$$
Multi Pack: Introduction to Automata Theory,...
Paperback
$$$$
Concrete Mathematics
Save
Provides a rigorous foundation in discrete mathematics, which is essential for understanding the theoretical foundations of computer science. It valuable resource for students who want to learn more about the mathematical underpinnings of algorithms and data structures.
Concrete Mathematics: A Foundation for Computer...
Kindle Edition
$$$
Cover image
Data Structures and Algorithm Analysis in Java
Save
This textbook provides a comprehensive introduction to data structures and algorithm analysis in Java. It good resource for students who want to learn more about the design and analysis of algorithms.
Data Structures and Algorithm Analysis in Java....
Paperback
$$$
Data Structures and Algorithm Analysis in Java
Hardcover
$$
Cover image
Automata Theory
Save
This textbook provides a comprehensive introduction to the theory of computation. It good resource for students who want to learn more about the theoretical foundations of computer science.
Automata Theory: An Algorithmic Approach
Hardcover
$$$
Automata Theory: An Algorithmic Approach
Kindle Edition
$$
Cover image
Algorithms
Save
Provides a comprehensive overview of algorithms and data structures, with a focus on their implementation in C++. It valuable resource for students and practitioners who want to learn more about the practical aspects of algorithm design.
Algorithms (4th Edition)
Hardcover
$$$
Algorithms, Fourth Edition: Book and 24-Part...
Hardcover
$$$$
Algorithms: Part I
Kindle Edition
$$
Algorithms, Part II
Kindle Edition
$$
(中文) Algorithms (4th Edition)(Chinese Edition)
Paperback
$$
Cover image
Essential Algorithms
Save
Provides a practical introduction to algorithms and data structures, with a focus on their implementation in Python and C++. It valuable resource for students and practitioners who want to learn more about the practical aspects of algorithm design.
Essential Algorithms: A Practical Approach to...
Paperback
$$
Essential Algorithms W / Ws
Paperback
$$$$
Essential Algorithms: A Practical Approach to...
Kindle Edition
$$
Cover image
Data Structures and Algorithms in Java
Save
Provides a comprehensive overview of data structures and algorithms, with a focus on their implementation in Python. It valuable resource for students and practitioners who want to learn more about the practical aspects of algorithm design.
Data Structures and Algorithms in Java
Paperback
Check
Data Structures and Algorithms in Java
Kindle Edition
Check
Cover image
Data Structures & Algorithms in Python
Save
Provides a comprehensive overview of algorithms and data structures, with a focus on their implementation in Java. It valuable resource for students and practitioners who want to learn more about the practical aspects of algorithm design.
Data Structures & Algorithms in Python
Paperback
Check
Data Structures & Algorithms in Python
Kindle Edition
Check

Share

Help others find this course page by sharing it with your friends and followers:
Facebook
LinkedIn
Reddit
X
Link
Email

Similar courses

Similar courses are unavailable at this time. Please try again later.
Via
Udacity
Instructors
Sebastian Wernicke
Sean Bennett
Sarah Norell
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Introduces theoretical computer science and its applications in algorithm problem-solving
Covers fundamental concepts like algorithm analysis, complexity, and NP-completeness
Taught by experienced instructors from Udacity
Provides a solid foundation for further studies in computer science
Requires basic programming knowledge and mathematical maturity
May require additional resources for deeper understanding of the concepts
Share this
Share to help others discover this course.
Facebook LinkedIn X Reddit Link Email
Begin learning today
Enroll now to gain full access to Intro to Theoretical Computer Science.
Enroll now
Save for later
Add this course to your list. Find it anytime.
Save
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser