Intro to Theoretical Computer Science | Dealing with Challenging Problems
Details
This class teaches you about basic concepts in theoretical computer science -- such as NP-completeness -- and what they imply for solving tough algorithmic problems.
At the end of this course, you will have a solid understanding of theoretical computer science. This will not only allow you to recognize some of the most challenging algorithmic problems out there, but also give you powerful tools to deal with them in practice.
You should have a basic understanding of algorithms (such as CS215) and programming (such as CS101). No prior knowledge about theoretical computer science required!
Outline
An introduction to tough problems and their analysis
Lesson 2: Understanding HardnessWhat we mean when a problem is “hard” and the concept of NP-completeness
Lesson 3: Showing HardnessTools to let you recognize and prove that a problem is hard
Lesson 4: Intelligent ForceSmart techniques to solve problems that should – theoretically – be impossible to solve
Lesson 5: Sloppy SolutionsGaining speed by accepting approximate solutions
Lesson 6: Poking AroundWhy randomness can be of help – sometimes. An introduction to complexity classes.
Lesson 7: Ultimate LimitsProblems that no computer can ever solve. In theory.
Speaker/s
Sebastian studied Bioinformatics at Universität Tübingen and holds a Ph.D. from Universität Jena in Germany, where his research focused on finding efficient algorithms for computationally hard problems on biological networks. After several years of strategic consulting for pharma companies and financial services, he's currently working with Seven Bridges Genomics, a big data bioinformatics startup. He is also well-known for his TED Talks, especially the one on the statistics of TED Talks..
Sean Bennett is a Course Architect at Udacity and is passionate about using the web to improve the quality of education available worldwide. Sean's background is in web programming, and he likes to dabble in functional web programming. When he's not working to improve education, Sean likes running, hiking, and preparing for the inevitable zombie apocalypse.
Sarah Norell holds a PhD in Mathematics from the University of London, UK. She has lectured at the London School of Economics, University of Umeå and Mid-Sweden University, and tutored all ages. Her breadth of experience at different levels has brought insight into some of the underlying problems students have with mathematics and it is this insight she brings to the courses here at Udacity.
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