Posted 06 March 2012 - 03:55 PM
Most of the courses from Udacity do not follow a university syllabus. That is not necessarily bad, however they are less in-depth than some of the other courses.
Building a search engine: - A programming and web development primer, a great project to get your feet wet in the web development world.
Web application engineering - A followup to "Building a search engine", although the more experienced web developers here may not gain much from it, it is an excellent way to for newer web developers to kick-start their web dev career.
Programming a robotic car - An introduction to AI and the practical application of these techniques, you build up a working program to accompany the theory that you learned in each lesson. It should be perfect for those who have been insterested in AI, but never studied it.
Programming languages - Covering programming language parsing and interpreting, you build a working web browser whilst learning the essentials of interpreting.
Applied cryptography - Both the theories behind cryptography, working programs and the applications in existing technologies including RSA and SSL.
Other Udacity courses coming soon:
- Theory of computation
- Operating Systems
- Computer Networks
- Distributed Systems
A few of the universities have got together to provide online courses similar to their full course. They will have higher starting requirements, however they will cover topics in more detail.
Design and analysis of algorithms - Mirroring the Stanford course, this should be useful for most of the non-CS majors at wdR.
Cryptography - Very similar to "Applied Cryptography", it will probably be slightly more in-depth. If you are unsure of which to choose, why not do both and decide once you have seen what both courses are like?
Natural language processing - Quite a few prerequisites are required for this course (Basic Calculus, probability theory, data structures and programming), however it should be able to pick up some of the background required as you go along.
Computer vision - Like "Natural Language Processing", this course requires some previous experience in Mathematics and programming at the level of a Junior Undergraduate.
Software as a service - Covers topics such as cloud computing as well as agile development, experience with an OOP programming language is recommended (the course is in Rails).
Human computer interaction - With a focus on web design, it covers the principles behind UI design and the techniques used to effectively turn ideas into prototypes and then complete designs.
Information theory - Information theory is applicable to a wide range of fields, and surprisingly this class does not have any other requirements apart from undergraduate mathematics.
Computer security - Complementing "Cryptography" quite nicely, it covers the entire spectrum of computer security, from memory vulnerabilities to network security. A background in C or C++ is expected.
Game theory - It may surprise some of you, but game theory is applicable to many fields, especially computer science. This course builds up from the basics, so it is accessible to pretty much anyone.
Probabilistic graphical models - A subset of ML (and AI), PGMs give you ways of dealing with uncertainty. During the course you also build several applications, including an OCR program and an action recognition program. Naturally, familiarity with basic probability is expected
CS 101 - By far the most basic course, it is more an introduction to computers and technology. Hopefully no one will need this course, but I put it here just in case
MITx only has one course at the moment. Depending on the success of this, MIT will decide whether they want to produce more of these courses.
Circuits and electronics - Not technically a computer science course, but still relevant to computer science and related subjects. It is an adaption of MIT's full course, so don't expect an easy ride (They expect you to require approximately 10 hours per week!).
Stanford (original) courses:
These three courses appeared long before the others, and have finished, however all of the material is still available.
Machine learning - A very broad introduction to Machine learning techniques, it focuses on both the theory and the implementation. There are no pre-requisites.
Introduction to databases - An in depth look at databases, covering both SQL and the newer NoSQL technologies, and the theories behind them.
Introduction to Artificial Intelligence - Arguably the course that started everything above. It is much closer to the Stanford course, so it is more in-depth than "Programming a robotic car".
- Stanford SEE
- Academic earth
- MIT Opencourseware
PS: If I have missed any out, please post with a link to the course (a couple of sentences detailing a summary of the course and any target audience would be nice ).
Posted 12 March 2012 - 02:30 PM
Posted 12 March 2012 - 02:55 PM
Oops, OpenCourseWare was already on the list. Anways - just wanted to recommend it
a hoopy frood who really knows where his towel is. ~~~ gibbonweb | github | hdr photography
my wife has a new DIY/decorations/floristry blog, wanna take a look? (stay tuned for English translations...)
Posted 19 May 2012 - 02:56 AM
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