Having a bit of trouble with self-learning from Cormen et al's algo book

Question

I started reading Intro to Algorithms by Cormen et al like 3 weeks ago on my free time. I finished the second chapter and have been trying out the exercises for quite a while. I find them a bit difficult.

Is this normal? Should I finish all the exercises before moving on? Or is it alright if I solve the ones I can and move on to the next chapters, possibly coming back to the exercises I can't figure out right now?

If anyone out there has had experience with this book, can you tell me how it was for you? I'm a bit discouraged on not being able to solve quite a few of the exercises here.

Answer 1

That book was hard for me too. We used it at the university I attended and I often had to refer to other sources to get simpler explanations when I found CLRS a little over my head. Once I got the Wikipedia explanation straight in my head, and a code sample working (which CLRS often lacks), I found that I was able to go back to the text and make sense of it.

Don't worry about doing all of the exercises. Even the super-elite MIT students don't have to do them all. Do what you can do and move on. If you need a concept in the next chapter that you had glossed over, it will still be there for you to backtrack to.

MIT OpenCourseWare has also made available the old lectures for Introduction to Algorithms (SMA 5503).

Answer 2

Good for you for diving into CLRS by yourself. You're a braver man than me. I used the book for a grad algorithms course I took last semester, and I had a hard time just finishing the problem sets assigned for the course. Completing all of the exercises would be a truly Herculean effort.

I'd recommend tackling the chapters that interest you most and those that you don't find to difficult. The beginning of the book, if I remember correctly, is one of the harder parts, diving into the mathematical background of a lot of different areas of algorithms. Chapter 5 is especially difficult unless you know a fair bit of probability theory. Also, starred sections and problems are significantly more challenging than the surrounding material (like 21.4, which contains material our professor confessed to being unable to prove in class). Finally at the end of the book, there is just a survey of miscellaneous topics; you can just look at those that interest you, since there are entire books written about each of those topics if you want to learn more about them.

I hope this helps, and most importantly, don't get too discouraged! This is the seminal book on algorithms for a reason.