awesome-courses/README.md

List of awesome Computer Science courses scoured from university pages across the web

Systems

• CS425 Distributed Systems Univ of Illinois, Urbana-Champaign
  • Brilliant set of lectures and reading material covering fundamental concepts in distributed systems such as Vector clocks, Consensus and Paxos.
  • Lectures
  • Assignments
• CS241 Systems Programming Univ of Illinois, Urbana-Champaign
  • Learn how to write programs that take full advantage of operating system support in the C programming language
  • Assignments
• 15-440 Distributed Systems Carnegie-Mellon University
  • Introduction to distributed systems with a focus on teaching concepts via projects implemented in the Go programming language.
  • Assignments
• SPAC Parallelism and Concurrency Univ of Washington
  • Technically not a course nevertheless an awesome collection of materials used by Prof Dan Grossman to teach parallelism and concurrency concepts to sophomores at UWash
• 15-749 Engineering Distributed Systems Carnegie-Mellon University
  • A project focused course on Distributed Systems with an awesome list of readings
  • Readings
• PODC Principles of Distributed Computing ETH-Zurich
  • Explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing in an easy-to-read set of lecture notes, combined with complete exercises and solutions.
  • Book
  • Assignments and Solutions
• CS5412 Cloud Computing Cornell University
  • Taught by one of the stalwarts of this field, Prof Ken Birman, this course has a fantastic set of slides that one can go through. The Prof's book is also a gem and recommended as a must read in Google's tutorial on Distributed System Design
  • Slides

Programming Languages / Compilers

• COS326 Functional Programming Princeton University
  • Covers functional programming concepts like closures, tail-call recursion & parallelism using the OCaml programming language
  • Lectures
  • Assignments
• CIS194 Introduction to Haskell Penn Engineering
  • Explore the joys of functional programming, using Haskell as a vehicle. The aim of the course will be to allow you to use Haskell to easily and conveniently write practical programs.
  • Previous semester also available, with more exercices
  • Assignments & Lectures
• CS240h Functional Systems in Haskell Stanford University
  • Building software systems in Haskell
  • Lecture Slides
  • 3 Assignments: Lab1, Lab2, Lab3
• CS164 Hack your language! UC Berkeley
  • Introduction to programming languages by designing and implementing domain-specific languages.
  • Lecture Videos
  • Code for Assignments
• CS3110 Data Structures and Functional Programming Cornell University
  • Another course that uses OCaml to teach alternative programming paradigms, especially functional and concurrent programming.
  • Lecture Slides
  • Assignments
• CS173 Programming Languages Brown University
  • Course by Prof. Krishnamurthi (author of HtDP) and numerous other awesome books on programming languages. Uses a custom designed Pyret programming language to teach the concepts. There was an online class hosted in 2012, which includes all lecture videos for you to enjoy.
  • Videos
  • Assignments

Algorithms

• COS226 Data Structures and Algorithms Princeton University
  • The popular algorithms class covering most important algorithms and data structures in use on computers taught by Robert Sedgewick.
  • Assignments

Misc

• CS 5150 Software Engineering Cornell University
  • Introduction to the practical problems of specifying, designing, building, testing, and delivering reliable software systems
  • Lectures
• 15-781 Machine Learning Carnegie Mellon University
  • Taught by one of the leading experts on Machine Learning - Tom Mitchell
  • Lectures
  • Project Ideas and Datasets
• ESM 296-4F GIS & Spatial Analysis UC Santa Barbara
  • Taught by James Frew, Ben Best, and Lisa Wedding
  • Focuses on specific computational languages (e.g., Python, R, shell) and tools (e.g., GDAL/OGR, InVEST, MGET, ModelBuilder) applied to the spatial analysis of environmental problems
  • GitHub (includes lecture materials and labs)