A Self-Learning, Modern Computer Science Curriculum was mentioned at Hacker News and provides links to resources for the following topics:

How to Learn
Intro to Computation
Some Additional Optional Intros
Common Lisp Intro
Little Schemer Series
Carnegie Mellon University
Elementary Math
Nonexistent Math Background
Weak/Forgotten Math Background
Calculus With Theory
Functional Programming
Principles of Functional Programming
Intro to Programming using OCaml
Linear Algebra
Abstract Algebra
Discrete Mathematics
Introduction to Pure Mathematics
Discrete Math with Standard ML
Great Theoretical Ideas in Computer Science
Computer Systems
Designing Systems
Database Systems
Practical Data Science
Meta-Linguistic Abstraction
Natural Language Processing
Programming Language Theory
Isolating Software Failure, Proving Safety and Testing
Physical Systems Software Security
Introduction to Parallel and Sequential Algorithms
Advanced Algorithms (Purely Functional Data Structures)
Complexity Theory
Undergraduate Complexity Theory
Graduate Complexity Theory
Useful Math for Theoretical CS
Introduction to Quantum Computing
Graduate Research in Type Theory
Basic Proof Theory
Intro to Category Theory
Type Theory Foundations
Higher Dimensional Type Theory
Further Research
Graduate Research in Machine Learning/AI
Graduate Introduction to General AI
Math Background for ML
Statistics Theory
Graduate Introduction to ML
Advanced Introduction to ML
Convex Optimization
Deep Learning
Algorithms for Big Data
Further Research
Graduate Research Elective: Cryptography
Graduate Cryptography Intro
Applied Cryptography
Future Research