There is a lot of ~~hidden~~ treasure lying within university pages scattered across the internet. This list is an attempt to bring to light those awesome courses which make their high-quality material i.e. assignments, lectures, notes, readings & examinations available online for free.
- 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.
- This class introduces the basic facilities provided in modern operating systems. The course divides into three major sections. The first part of the course discusses concurrency. The second part of the course addresses the problem of memory management. The third major part of the course concerns file systems.
- [CS 162](http://cs162.eecs.berkeley.edu/) **Operating Systems and Systems Programming***UC Berkeley*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png"width="20"height="20"alt="Lecture Videos"title="Lecture Videos"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png"width="20"height="20"alt="Readings"title="Readings"/>
- In the project assignments in CS186, you will write a basic database management system called SimpleDB. For this project, you will focus on implementing the core modules required to access stored data on disk; in future projects, you will add support for various query processing operators, as well as transactions, locking, and concurrent queries.
- System programming refers to writing code that tasks advantage of operating system support for programmers. This course is designed to introduce you to system programming. By the end of this course, you should be proficient at writing programs that take full advantage of operating system support. To be concrete, we need to fix an operating system and we need to choose a programming language for writing programs. We chose the C language running on a Linux/UNIX operating system (which implements the POSIX standard interface between the programmer and the OS).
- Brilliant set of lectures and reading material covering fundamental concepts in distributed systems such as Vector clocks, Consensus and Paxos. This is the 2014 version by Prof Indranil Gupta.
- Write a real-time OS microkernel in C, and application code to operate a model train set in response to real-time sensor information. The communication with the train set runs at 2400 baud so it takes about 61 milliseconds to ask all of the sensors for data about the train's possible location. This makes it particularly challenging because a train can move about 3 centimeters in that time. One of the most challenging and time-consuming courses at the University of Waterloo.
- A course (that) covers topics including: Analysis process communication and synchronization; resource management; virtual memory management algorithms; file systems; and networking and distributed systems. The primary goal of this course is to improve your ability to build scalable, robust and secure computing systems. It focuses on doing that by understanding what underlies the core abstractions of modern computer systems.
- 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)
- [CSCE 3613](http://comp.uark.edu/~wingning/csce3613/csce3613.html) **Operating Systems***University of Arkansas (Fayetteville)*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png"width="20"height="20"alt="Readings"title="Readings"/>
- An introduction to operating systems including topics in system structures, process management, storage management, files, distributed systems, and case studies.
- 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.
- [ECE 459](http://patricklam.ca/p4p/) **Programming for Performance***University of Waterloo*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- Learn techniques for profiling, rearchitecting, and implementing software systems that can handle industrial-sized inputs, and to design and build critical software infrastructure. Learn performance optimization through parallelization, multithreading, async I/O, vectorization and GPU programming, and distributed computing.
- 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.
- [SPAC](http://homes.cs.washington.edu/~djg/teachingMaterials/spac/) **Parallelism and Concurrency***Univ of Washington*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png"width="20"height="20"alt="Readings"title="Readings"/>
- 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
- MIT's operating systems course focusing on the fundamentals of OS design including booting, memory management, environments, file systems, multitasking, and more. In a series of lab assignments, you will build JOS, an OS exokernel written in C.
- Very comprehensive material on Computer Architecture - definitely more than just "introduction". Online material is very user-friendly, even the recitation videos available online. This is the Spring'14 version by Prof. [Onur Mutlu ](http://users.ece.cmu.edu/~omutlu/)
- 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](http://www.seas.upenn.edu/~cis194/spring13/index.html) semester also available, with more exercises
- [Clojure](http://mooc.cs.helsinki.fi/clojure) **Functional Programming with Clojure***University of Helsinki*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/>
- The course is an introduction to functional programming with a dynamically typed language Clojure. We start with an introduction to Clojure; its syntax and development environment. Clojure has a good selection of data structures and we cover most of them. We also go through the basics of recursion and higher-order functions. The course material is in English.
- 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.
- [CS 240h](http://www.scs.stanford.edu/14sp-cs240h/) **Functional Systems in Haskell***Stanford University*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- [CS 421](https://courses.engr.illinois.edu/cs421/fa2014/) **Programming Languages and Compilers***Univ of Illinois, Urbana-Champaign*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png"width="20"height="20"alt="Lecture Videos"title="Lecture Videos"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- [CS 4610](http://www.cs.virginia.edu/~weimer/4610/) **Programming Languages and Compilers***University of Virginia*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- Course that uses OCaml to teach functional programming and programming language design. Each assignment is a part of an interpreter and compiler for an object-oriented language similar to Java, and you are required to use a different language for each assignment (i.e., choose 4 from Python, JS, OCaml, Haskell, Ruby).
- If you're a fan of Prof Matt's writing on his [fantastic blog](http://matt.might.net/articles/) you ought to give this a shot. The course covers the design and implementation of compilers, and it explores related topics such as interpreters, virtual machines and runtime systems. Aside from the Prof's witty take on [cheating](http://matt.might.net/teaching/compilers/spring-2015/#collaboration) the page has tons of interesting links on programming languages, parsing and compilers.
- 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.
- Algorithms class covering recursion, randomization, amortization, graph algorithms, network flows and hardness. The lecture notes by Prof. Erikson are comprehensive enough to be a book by themselves. Highly recommended!
- 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.
- [Lectures and Assignments](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci135/csci135_36_fall12.php)
- 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.
- [Lectures and Assignments](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci235/csci235_f14.php)
- 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.
- [Lectures and Assignments](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci335/csci335_s14.php)
- Prof Steven Skiena's no stranger to any student when it comes to algorithms. His seminal [book](http://www.algorist.com/) has been touted by many to be best for [getting that job in Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html). In addition, he's also well-known for tutoring students in competitive [programming competitions](http://www.programming-challenges.com/pg.php?page=index). If you're looking to brush up your knowledge on Algorithms, you can't go wrong with this course.
- Taught by [Dan Gusfield](http://web.cs.ucdavis.edu/~gusfield/) in 2010, this course is an undergraduate introduction to algorithm design and analysis. It features traditional topics, such as Big Oh notation, as well as an importance on implementing specific algorithms. Also featured are sorting (in linear time), graph algorithms, depth-first search, string matching, dynamic programming, NP-completeness, approximation, and randomization.
- This is the graduate level complement to the ECS 122A undergraduate algorithms course by [Dan Gusfield](http://web.cs.ucdavis.edu/~gusfield/) in 2011. It assumes an undergrad course has already been taken in algorithms, and, while going over some undergraduate algorithms topics, focuses more on increasingly complex and advanced algorithms.
- [6.INT](http://courses.csail.mit.edu/iap/interview/index.php) **Hacking a Google Interview***MIT*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png"width="20"height="20"alt="Readings"title="Readings"/>
- This course taught in the MIT Independent Activities Period in 2009 goes over common solution to common interview questions for software engineer interviews at highly selective companies like Apple, Google, and Facebook. They cover time complexity, hash tables, binary search trees, and other common algorithm topics you should have already covered in a different course, but goes more in depth on things you wouldn't otherwise learn in class- like bitwise logic and problem solving tricks.
- This is an advanced DS course, you must be done with the [Advanced Algorithms](http://courses.csail.mit.edu/6.854/current/) course before attempting this one.
- [Lectures](http://courses.csail.mit.edu/6.851/spring14/lectures/) Contains videos from sp2012 version, but there isn't much difference.
- [Assignments](http://courses.csail.mit.edu/6.851/spring14/hmwk.html) contains the calendar as well.
- Advanced course in algorithms by Dr. David Karger covering topics such as amortization, randomization, fingerprinting, word-level parallelism, bit scaling, dynamic programming, network flow, linear programming, fixed-parameter algorithms, and approximation algorithms.
- **Register** on [NB](http://nb.mit.edu/subscribe?key=D3a8CYpoO2VcR1ZcfaxmR5KbyjCGXd3INNXvL3mxEakYJ7qGJw) to access the [problem set and lectures](http://nb.mit.edu/).
- The required algorithms class that go in depth into all basic algorithms and the proofs behind them. This is one of the heavier algorithms curriculums on this page. Taught by Avrim Blum and [Manuel Blum](http://en.wikipedia.org/wiki/Manuel_Blum) who has a Turing Award due to his contributions to algorithms. Course link includes a very comprehensive set of reference notes by Avrim Blum.
- 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)
- CS103 is a first course in discrete math, computability theory, and complexity theory. In this course, we'll probe the limits of computer power, explore why some problems are harder to solve than others, and see how to reason with mathematical certainty.
- Links to all lectures notes and assignments are directly on the course page
- [CS 173](https://courses.engr.illinois.edu/cs173/fa2014/A-lecture/index.html) **Discrete Structures***Univ of Illinois Urbana-Champaign*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png"width="20"height="20"alt="Readings"title="Readings"/>
- This course is an introduction to the theoretical side of computer science. In it, you will learn how to construct proofs, read and write literate formal mathematics, get a quick introduction to key theory topics and become familiar with a range of standard mathematics concepts commonly used in computer science.
- This course discusses the complexity-theory foundations of modern cryptography, and looks at recent results in the field such as Fully Homomorphic Encryption, Indistinguishability Obfuscation, MPC and so on.
- An graduate level course on complexity theory that introduces P vs NP, the power of randomness, average-case complexity, hardness of approximation, and so on.
- CS 498 section 374 (unofficially "CS 374") covers fundamental tools and techniques from theoretical computer science, including design and analysis of algorithms, formal languages and automata, computability, and complexity. Specific topics include regular and context-free languages, finite-state automata, recursive algorithms (including divide and conquer, backtracking, dynamic programming, and greedy algorithms), fundamental graph algorithms (including depth- and breadth-first search, topological sorting, minimum spanning trees, and shortest paths), undecidability, and NP-completeness. The course also has a strong focus on clear technical communication.
- Programming in different paradigms with emphasis on object oriented programming, network programming and functional programming. Survey of programming languages, event driven programming, concurrency, software validation.
- [CS 10](https://inst.eecs.berkeley.edu/~cs10/fa14/) **The Beauty and Joy of Computing***UC Berkeley*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png"width="20"height="20"alt="Lecture Videos"title="Lecture Videos"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- CS10 is UCB's introductory computer science class, taught using the beginners' drag-and-drop language. Students learn about history, social implications, great principles, and future of computing. They also learn the joy of programming a computer using a friendly, graphical language, and will complete a substantial team programming project related to their interests.
- [Snap*!*](http://snap.berkeley.edu) (based on Scratch by MIT).
- 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++)
- Introductory course for students majoring in computer science or computer engineering. Software development process: problem specification, program design, implementation, testing and documentation. Programming topics: data representation, conditional and iterative statements, functions, arrays, strings, file I/O, and classes. Using C++ in a UNIX environment.
- This course continues developing problem solving techniques by focusing on fundamental data structures and associated algorithms. Topics include: abstract data types, introduction to object-oriented programming, linked lists, stacks, queues, hash tables, binary trees, graphs, recursion, and searching and sorting algorithms. Using C++ in a UNIX environment.
- Teaches big-picture computing concepts using the Scheme programming language. Students will implement programs in a variety of different programming paradigms (functional, object-oriented, logical). Heavy emphasis on function composition, code-as-data, control abstraction with continuations, and syntactic abstraction through macros. An excellent course if you are looking to build a mental framework on which to hang your programming knowledge.
- The course presents the subject through a series of seminars and labs, which will explore it from its early beginnings, and work themselves to some of the state of the art. The seminars will cover the basics of deep learning and the underlying theory, as well as the breadth of application areas to which it has been applied, as well as the latest issues on learning from very large amounts of data. We will concentrate largely, although not entirely, on the connectionist architectures that are most commonly associated with it. *Lectures* and *Reading Notes* are available on the page.
- Learning from data in order to gain useful predictions and insights. This course introduces methods for five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.
- Course taught by [Tony Jebara](http://www.cs.columbia.edu/~jebara/resume.html) introduces topics in Machine Learning for both generative and discriminative estimation. Material will include least squares methods, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models, hidden Markov models, support vector machines, and kernel methods.
- [Lectures and Assignments](http://www.cs.columbia.edu/~jebara/4771/handouts.html)
- The course concentrates on recognizing and solving convex optimization problems that arise in applications. Topics addressed include the following. Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interior-point methods. Applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.
- An introductory course in computer vision and computational photography focusing on four topics: image features, image morphing, shape matching, and image search.
- Course taught by [W. Owen Redwood](http://ww2.cs.fsu.edu/~redwood/) and [Xiuwen Liu](http://www.cs.fsu.edu/~liux/). It covers a wide range of computer security topics, starting from Secure C Coding and Reverse Engineering to Penetration Testing, Exploitation and Web Application Hacking, both from the defensive and the offensive point of view.
- [Lectures and Videos](http://www.cs.fsu.edu/~redwood/OffensiveComputerSecurity/lectures.html)
- [CS 75](http://ocw.tufts.edu/Course/75) **Introduction to Game Development***Tufts University*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- The course taught by [Ming Y. Chow](http://mchow01.github.io) teaches game development initially in PyGame through Python, before moving on to addressing all facets of game development. Topics addressed include game physics, sprites, animation, game development methodology, sound, testing, MMORPGs and online games, and addressing mobile development in Android, HTML5, and iOS. Most to all of the development is focused on PyGame for learning principles
- This is a course on how to be a hacker. Your first four homework assignments walk you through the process of building your own unix shell. You'll be developing it as an open source project, and you will collaborate with each other at various points.
- Updated for iOS 7. Tools and APIs required to build applications for the iPhone and iPad platform using the iOS SDK. User interface designs for mobile devices and unique user interactions using multi-touch technologies. Object-oriented design using model-view-controller paradigm, memory management, Objective-C programming language. Other topics include: object-oriented database API, animation, multi-threading and performance considerations.
- Prerequisites: C language and object-oriented programming experience
- 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.
- [CS 378](https://github.com/ut-cs378-vision-2014fall/course-info) **3D Reconstruction with Computer Vision***UTexas*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- In this lab-based class, we'll dive into practical applications of 3D reconstruction, combining hardware and software to build our own 3D environments from scratch. We'll use open-source frameworks like OpenCV to do the heavy lifting, with the focus on understanding and applying state-of-the art approaches to geometric computer vision
- Taught by [J. Alex Halderman](https://jhalderm.com/) who has analyzed the security of Electronic Voting Machines in the [US](https://jhalderm.com/pub/papers/dcvoting-fc12.pdf) and [over](https://jhalderm.com/pub/papers/ivoting-ccs14.pdf) [seas](https://jhalderm.com/pub/papers/evm-ccs10.pdf).
- This intensive research seminar covers foundational work and current topics in computer systems security.
- 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)
- Taught by [Philip Johnson](http://philipmjohnson.org/)
- Introduction to software engineering using the ["Athletic Software Engineering" pedagogy](http://philipmjohnson.org/2013/12/16/athletic-software-engineering-education-initial-results/)
- [IGME 582](http://hfoss-fossrit.rhcloud.com) **Humanitarian Free & Open Source Software Development***Rochester Institute of Technology*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
- 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.
- Course taught by [Luis Rocha](http://www.informatics.indiana.edu/rocha/lr_form.html) about the multi-disciplinary field algorithms inspired by naturally occurring phenomenon. This course provides introduces the following areas: L-systems, Cellular Automata, Emergence, Genetic Algorithms, Swarm Intelligence and Artificial Immune Systems. It's aim is to cover the fundamentals and enable readers to build up a proficiency in applying various algorithms to real-world problems.
- [Open Sourced Elective: Database and Rails](http://www.schneems.com/ut-rails/) **Intro to Ruby on Rails***University of Texas*<imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png"width="20"height="20"alt="Lecture Videos"title="Lecture Videos"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png"width="20"height="20"alt="Assignments"title="Assignments"/><imgsrc="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png"width="20"height="20"alt="Lecture Notes"title="Lecture Notes"/>
