It gives you questions that you write programs to solve, then judges your programs against test cases. It's fantastic. The questions are difficult, but never impossible, and they drill you well on diverse algorithms, building on previously learned concepts, so that you really understand the material.
Recently, however, I came across the following gem: Algorihtms + Data Structures = Programs, by Niklaus Wirth. (an Oberon version of 1994 is available for free: http://www.oberon.ethz.ch/WirthPubl/AD.pdf). I think this is hands down one of the best algorithm books. It amazes me how much content Niklaus Wirth is able to present in concise, yet crystal clear writing. Besides the usual algorithms, he includes very interesting applications that probably no other book does: using the partitioning of QuickSort to find the median (pg. 56 in above PDF, Section 2.3.4), based on algorithm by C.A.R. Hoare, and an in-depth discussion of polyphase sort (pg. 70, Section 2.4.4), which might be interesting for heavily distributed sorting (that at least what I imagined as a possible application when I recently re-read parts of it).
The whole point of big encyclopedic texts like Cormen et al. is to wet your feet and give you a broad exposure to various techniques. That way you have a small idea on what you want to use next, and you know which domain to focus your research.
My one recommendation is to ditch programming languages with huge boot-times when playing with algorithms. You want something that you can interact with live and see results; in that regard, even a symbolic algebra system like Maxima would be better than C, C++ and Java. Lisp and Python would be ideal for most algorithms.