Algorithmic Design and Techniques
Data Structures Fundamentals
Graph Algorithms
NP-Complete Problems
String Processing and Pattern Matching Algorithms
Dynamic Programming: Applications In Machine Learning and Genomics
Graph Algorithms in Genome Sequencing
Algorithms and Data Structures Capstone
Very little of which is communicated in any way to help someone learn how compilers work.
In the actual history of computing very few good compilers were ever written by algorithm and data structures professors; most were written by people who had a pragmatic drive to get something done. Theory is good but without practice it is little more than navel gazing. Theory and practice need each other.
The reason that nand2tetris works so well as a course is that it gives you a concrete example of how all these algorithms and data structures are combined in order to turn an abstract description (the source code) into a running program that also includes how that computing is achieved through compiler, assembler, linker, run time, operating system, isa, and finally in transistors.
The true issue it gets to is that most programmers have very little understanding of how computers actually work, and when things break they just do high order guessing to get things working again rather than truly understanding what went wrong.
As an EE undergrad, I had to design a TTL based processor, program the microcode, etc. I have no idea how a compiler works, or anything above assembly.
Comprises the following courses
Algorithmic Design and Techniques Data Structures Fundamentals Graph Algorithms NP-Complete Problems String Processing and Pattern Matching Algorithms Dynamic Programming: Applications In Machine Learning and Genomics Graph Algorithms in Genome Sequencing Algorithms and Data Structures Capstone