- [SPAC](http://homes.cs.washington.edu/~djg/teachingMaterials/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
- 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.
- 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](http://www.amazon.com/Guide-Reliable-Distributed-Systems-High-Assurance/dp/1447124154) is also a gem and recommended as a must read in Google's tutorial on [Distributed System Design](http://www.hpcs.cs.tsukuba.ac.jp/~tatebe/lecture/h23/dsys/dsd-tutorial.html)
- A course that is mostly about writing programs against the UNIX API, covering all of the basic parts of the kernel interface and libraries, including files, processes, terminal control, signals, and threading.
- The course is an introduction to parallel algorithms and parallel programming in C and C++, using the Message Passing Interface (MPI) and the OpenMP application programming interface. It also includes a brief introduction to parallel architectures and interconnection networks. It is both theoretical and practical, including material on design methodology, performance analysis, and mathematical concepts, as well as details on programming using MPI and OpenMP.
- CS107 is the third course in Stanford's introductory programming sequence. The course will work from the C programming language down to the microprocessor to de-mystify the machine. With a complete understanding of how computer systems execute programs and manipulate data, you will become a more effective programmer, especially in dealing with issues of debugging, performance, portability, and robustness. Topics covered include: the C programming language, data representation, machine-level code, computer arithmetic, elements of code compilation, optimization of memory and runtime performance, and memory organization and management.
- 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.
- Course by Prof. Krishnamurthi (author of [HtDP](http://htdp.org/2003-09-26/Book/)) and numerous other [awesome](http://cs.brown.edu/courses/cs173/2012/book/) [books](http://papl.cs.brown.edu/2014/index.html) on programming languages. Uses a custom designed [Pyret](http://www.pyret.org/) programming language to teach the concepts. There was an [online class](http://cs.brown.edu/courses/cs173/2012/OnLine/) hosted in 2012, which includes all lecture videos for you to enjoy.
- [COS226](http://www.cs.princeton.edu/courses/archive/fall14/cos226/info.php) **Data Structures and Algorithms***Princeton University*
- The [popular](https://www.coursera.org/course/algs4partI) algorithms class covering most important algorithms and data structures in use on computers taught by Robert Sedgewick.
- In this course, you will study advanced programming techniques including data structures, encapsulation, abstract data types, interfaces, and algorithms for sorting and searching, and you will get a taste of “software engineering”—the design and implementation of large programs.
- [CSCI 135](http://compsci.hunter.cuny.edu/~sweiss/courses/csci135.php) **Software Design and Analysis I**
*CUNY Hunter College*
- It is currently an intensive introduction to program development and problem solving. Its emphasis is on the process of designing, implementing, and evaluating small-scale programs. It is not supposed to be a C++ programming course, although much of the course is spent on the details of C++. C++ is an extremely large and complex programming language with many features that interact in unexpected ways. One does not need to know even half of the language to use it well.
- Introduces algorithms for a few common problems such as sorting. Practically speaking, it furthers the students' programming skills with topics such as recursion, pointers, and exception handling, and provides a chance to improve software engineering skills and to give the students practical experience for more productive programming.
- This includes the introduction of hashes, heaps, various forms of trees, and graphs. It also revisits recursion and the sorting problem from a higher perspective than was presented in the prequels. On top of this, it is intended to introduce methods of algorithmic analysis.
- [CIS 500](http://www.seas.upenn.edu/~cis500/cis500-f14/index.html) **Software Foundations***University of Pennsylvania*
- An introduction to formal verification of software using the Coq proof assistant. Topics include basic concepts of logic, computer-assisted theorem proving, functional programming, operational semantics, Hoare logic, and static type systems.
* [Lectures and Assignments](http://www.seas.upenn.edu/~cis500/cis500-f14/index.html#schedule)
- [CS 10](https://inst.eecs.berkeley.edu/~cs10/fa14/) **The Beauty and Joy of Computing***UC Berkeley*
- CS10 is UCB's introductory computer science class, taught using the beginners' drag-and-drop language [Snap*!*](http://snap.berkeley.edu) (based on Scratch by MIT).
- [CS 50](https://cs50.harvard.edu/) **Introduction to Computer Science***Harvard University*
- CS50x is Harvard College's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan.
- CS101 teaches the essential ideas of Computer Science for a zero-prior-experience audience. Participants play and experiment with short bits of "computer code" to bring to life to the power and limitations of computers.
- Lectures videos will available for free after registration.
- This course is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Programming Methodology teaches the widely-used Java programming language along with good software engineering principles.
- This course is the natural successor to Programming Methodology and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming language, which is similar to both C and Java.
- Topics: Advanced memory management features of C and C++; the differences between imperative and object-oriented paradigms. The functional paradigm (using LISP) and concurrent programming (using C and C++)
- [ESM 296-4F](http://ucsb-bren.github.io/esm296-4f/) **GIS & Spatial Analysis***UC Santa Barbara*
- Taught by [James Frew](http://www.bren.ucsb.edu/people/Faculty/james_frew.htm), [Ben Best](http://mgel.env.duke.edu/people/ben-best/), and [Lisa Wedding](http://www.centerforoceansolutions.org/team/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 ](http://ucsb-bren.github.io/esm296-4f/) (includes lecture materials and labs)
- This course provides students with exposure to the design, creation and production of Open Source Software projects. Students will be introduced to the historic intersections of technology and intellectual property rights and will become familiar with Open Source development processes, tools and practices.
- The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control.
- [CIS 581](https://alliance.seas.upenn.edu/~cis581/wiki/index.php?title=CIS_581:_Computer_Vision_%26_Computational_Photography) **Computer Vision and Computational Photography***University of Pennsylvania*
- An introductory course in computer vision and computational photography focusing on four topics: image features, image morphing, shape matching, and image search.