Illinois course materials
Lecture notes, slides, lab handouts, homeworks, and exams are
available for several past semesters of algorithms classes at
Illinois. For each class, I've listed only the most recent
iteration for each instructor, but several older semesters are also
Course materials elsewhere
Sadly, it has become significantly less common for instructors to post their lecture notes/slides, homeworks, lab handouts, and so on to the open web. Most(?) instructors either lock their course materials inside walled gardens (Piazza, Moodle, Stellar, etc.) or delete them entirely when the course is over. Here are some useful exceptions.
Course Notes for CSCB38/236/240 - Introduction to the theory of computation by
Vassos Hadzilacos. Excellent coverage of regular langauges
and expressions, DFAs and NFAs, and context-free langagues and grammars. Also includes an excellent review of induction, especially for proving correctness of algorithms.
Fall 2011) — notes, videos, and problem sets
— homeworks, occasional slides
Spring 2015) — notes/slides only
- Stanford (Summer 2013) — slides and problem sets
Washington (several quarters) — notes/slides, sporadic problem sets
- UC Davis (videos on iTunes):
and Udacity are offering
complete algorithms courses, with videos, readings, and
automatically graded exercises. By necessity, these courses tend to
focus more on implementation and less on proofs and open-ended
design than CS 374 or 473. I have included only MOOCs with videos
that are always freely available.
- Algorithms: Design and Analysis
and Part 2,
taught by Tim Roughgarden, loosely based on algorithms classes
- Algorithms, taught by Michael Littman,
loosely based on algorithms classes at Rutgers
to Theoretical Computer Science, taught
by Sebastian Wernicke
compiled by Bhanu Kapoor. Included for completeness, but good
only for review of the most basic material.
For students who prefer an actual dead-tree reference, we recommend
the following textbooks. The campus bookstore probably doesn't have
them, but they're cheaper online anyway. I've asked Grainger
Library to put copies of all these books on reserve.
Algorithm Design by Jon Kleinberg and Éva Tardos
(Addison-Wesley, 2005). Based on algorithms classes at Cornell.
- Algorithms by Sanjoy Dasgupta, Christos
Papadimitriou, and Umesh Vazirani (McGraw-Hill, 2006). Based on
the undergraduate algorithms course at Berkeley.
A complete draft of the book is available online. This is
the closest traditionally published approximation to the
old CS 473 and the algorithms portion of CS 374.
- Introduction to Algorithms (3rd edition) by
Thomas H. Cormen, Charles Leiserson, Ronald L. Rivest, and
Clifford Stein (MIT Press/McGraw-Hill, 2009). Based on
algorithms classes at MIT. The first and second editions are
also fine. A significant fraction of this book has been
- Algorithms (5th edition) by Robert Sedgewick
and Kevin Wayne (Addison-Wesley, 2011). Based on algorithms
classes at Princeton. Focuses on more elementary material
(taught in CS 225), with more emphasis on implementation and
application than open-ended design and analysis.
A crippled electronic version is available
through the University library (sorry, only for
For review of prerequisite material, we strongly recommend the
following online resources. (This stuff is also covered in
several dead-tree textbooks, but really, why bother?)
...which (at least at the advanced levels) are really algorithm design contests where you also happen to write some code.
We'll add more links here as we discover them.
Suggestions are welcome!
Last modified: Wed Aug 21:40:02 UTC 2017 by Sariel Har-Peled