Over the summer, Stanford announced that they would be offering their AI class online for free. It made headlines, and a few weeks later they announced that they would be offering their intro to databases class and their machine learning class as well.
Introduction to DataBases: :)
The database class is the most accessible. It was a freshman class at Stanford, As with many CS classes, it certainly helps to have a strong background in discrete math. Specifically, prior exposure to mathematical logic, set theory, and relations makes it significantly easier to follow the discussions of relational algebra and relational design theory. The videos are fast-paced and interesting. The randomized quizzes that you can take over and over until you get 100% are a brilliant way to empower students to keep working until they have achieved mastery. The online homework system for practicing queries against a live database works quite well, and the exercises cover a nice range of difficulty from easy to hard. The teacher's weekly "screenside chats" and vibrant forum community really make it feel like you're "taking a class" rather than just working through a sterile set of videos and exercises. The material is well organized and is generally posted two to three weeks ahead of time for those who want to get ahead. the course took off discussing with relational databases, moving on to XML & JSON data, queryinig XML through Xpath., All in all, it's the best example I've ever seen of what online education can potentially be.
Those unpleasent experiences with DTD's and XSLT querying exercises are one thing i remember the most,:(
and the chick factor about taking this course is that... soon when i got to college with this new knowledge of databases.. i was awestuck to know that no one in our computerscience department knew about NoSql systems... :O suddenly i started to feel like i was no more the "regular conventional one" :)
Machine Learning: Basic non-programming. :(
The machine learning class is of similarly high quality, featured weekly programming assignments, using the free language Octave. The programming write-ups are very clear, and you can keep submitting your program until you get it perfect. The submission process is very easy. This class is a very math-centric approach to machine learning, and I think to fully appreciate the material you need to have a certain comfort level with the basics of linear algebra, and it helps to have seen multivariate calculus. I'm having mixed feelings right now.. the subject matter was really interesting.. it was suposed to be a graduate class at stanford..soo may be i need to feel much comfortable around and with computers and programming in general. I ever it is offered again.. i would really liek to work on he programming assignments as well..
Introduction to DataBases: :)
The database class is the most accessible. It was a freshman class at Stanford, As with many CS classes, it certainly helps to have a strong background in discrete math. Specifically, prior exposure to mathematical logic, set theory, and relations makes it significantly easier to follow the discussions of relational algebra and relational design theory. The videos are fast-paced and interesting. The randomized quizzes that you can take over and over until you get 100% are a brilliant way to empower students to keep working until they have achieved mastery. The online homework system for practicing queries against a live database works quite well, and the exercises cover a nice range of difficulty from easy to hard. The teacher's weekly "screenside chats" and vibrant forum community really make it feel like you're "taking a class" rather than just working through a sterile set of videos and exercises. The material is well organized and is generally posted two to three weeks ahead of time for those who want to get ahead. the course took off discussing with relational databases, moving on to XML & JSON data, queryinig XML through Xpath., All in all, it's the best example I've ever seen of what online education can potentially be.
Those unpleasent experiences with DTD's and XSLT querying exercises are one thing i remember the most,:(
and the chick factor about taking this course is that... soon when i got to college with this new knowledge of databases.. i was awestuck to know that no one in our computerscience department knew about NoSql systems... :O suddenly i started to feel like i was no more the "regular conventional one" :)
Machine Learning: Basic non-programming. :(
The machine learning class is of similarly high quality, featured weekly programming assignments, using the free language Octave. The programming write-ups are very clear, and you can keep submitting your program until you get it perfect. The submission process is very easy. This class is a very math-centric approach to machine learning, and I think to fully appreciate the material you need to have a certain comfort level with the basics of linear algebra, and it helps to have seen multivariate calculus. I'm having mixed feelings right now.. the subject matter was really interesting.. it was suposed to be a graduate class at stanford..soo may be i need to feel much comfortable around and with computers and programming in general. I ever it is offered again.. i would really liek to work on he programming assignments as well..
One thing that i learned most about these free online course's is... simple.. "I'm a different person that i was yesterday, regular college never taught me how to think in terms of solving real world problems " success slowly day by day..:)
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