That's more lectures than a student could see. Now we need a full concept chart dependency tree and an adaptive content suggestion system to guide students through this sea of lectures.<p>I'd like to have a system where you take tests to rate your understanding level and decide where to start.
One of my biggest complaints about a lot of the stuff found in YouTube is the lack of preparation.<p>Those without teaching experience think it is enough to fire-up the screen recorder and go for it. Sure, that can work, but it often results in a bad or mediocre product.<p>The most egregious of issues being when they destroy your concentration because they are making mistakes live as you follow along. "No! Wait! That was a period. No a slash. No, I forgot to define the class. Oh, yeah, the import was wrong. Wait, a database table is missing." ... and more.<p>Some could argue that this can be interesting because you see errors. Point taken. This is the wrong way to teach about errors. It destroys the student's train of thought and detracts from learning.<p>The right way to teach about errors it to explicitly teach them. In other words, you do it correctly and then say "let's see what happens if we delete this column in the database". You can then expose the issues and how to deal with them. To unexpectedly run into issues during a tutorial due to lack of preparation only confuses students. Imagine a Calculus professor fumbling as he/she explains course material, it would be maddening.<p>If you want to teach, please take the time to prepare the material and the script. Have at least a second monitor on your machine so you can view the script as you record your lesson on the main monitor. Never take students down a path you have to reverse from, it can be very confusing.<p>EDIT: By "script" I don't mean "code" but rather what you are going to say and do and when. Yes, you need to have your code visible on a separate monitor as well just to make sure you don't make mistakes.
I highly recommend MIT's 6.006 for a good intro to data structures and algorithms. My college's course wasn't great, but watching the MIT lectures and working through CLRS helped me gain a really solid intuitive understanding of complexity and approaches to different classes of problems. At the very least it helped a lot with interviews!
Excellent resource. I'm almost at the end of Andrew Ng's ML course on Coursera and was looking to learn more about convex optimization. I will definitely try out some of the links there (Machine Learning > misc machine learning topics)
Thanks for posting this. As a bootcamp grad, I just bought a Intro to CS textbook to start learning the basics, but I can't wait to look at some of these too
This is cool. I think "visual learners" or whatever it's called are a bit on the fringe in CS but we do exist. When starting something new, I learn much more easily by video or discussion with people. As I become more comfortable with a subject, technical documentation becomes progressively more useful.
I guess this shows how much of a commodity video lectures are. It's difficult to know the quality in advance of watching a video.<p>Teaching is a market for lemons. Worse, the student who buys a lemon will often not realize it, nor the employer who hires the lemon-trained student.<p>Most of the videos listed here are from reputable institutions. I guess we're lucky that the lemon-sellers are trying to profit from their videos.