I just finished the Machine Learning course on Coursera. Which is available for free. If you want a certificate you can pay for the course as well. But I personally didn’t. (Here is a post on the topic of paying for online courses. I do not want to discuss this here since this was my first online course.)

I actually studied for a lot of courses in my school from online sources. I usually do not follow the lectures on the school. (To be honest, “usually” meant whenever possible so far.) This has several reasons. Being able to learn at the speed you want, in the time you want etc. But the main reason was an observation I made in my first year. If a course is graded solely based on exams, one can learn (or memorize depending on the content) what is neccessary in a few days and get a good grade. Emphasis on good, not saying great. And those few days won’t be easy. Especially if you have many exams stacked upon each other in a single week. But it is doable. And actually going to lectures take more effort and time, which one can use for other things. (Like dying in Isaac, 15 times or so.)

But this was the first time I took an actual online course. I started the course as a part of my summer training at VR-Masters. Which is a whole other topic I should have written about. Anyway, the project I was given drastically changed after I started with the course. (Moved from AI to an ESP8266 project.) So the Machine Learning course became a personal objective for me. It is an 11-week course and I took a few more weeks than the intended time. Because, you know, summer.

I think the course went really well for me. I am really eager to apply machine learning to something like a Reddit bot to gain some practice on the subject. The course itself is not that hard and probably it meant much much more a few years ago. I would think it only gives you a base knowledge. Regardless, it teaches you intuition on the topic, does not just give you plain formulas and code. The last week of the course is all about debugging, optimization and problems that might arise when doing a practical application. I really recommend it to anyone who is just starting just starting out with machine learning. Don’t be scared if you have no previous knowledge on this subject. All you need is just a bit of linear algebra. And by a bit, I mean matrix multiplication and transposes. I can also recommend the MIT OpenCourseWare Linear Algebra course for starting with Linear Algebra, which was the content I used when I was studying for the Matrix Theory course at Boğaziçi.

This post was more for myself, I think. I felt like writing something that I could read in the future after finishing up with the course today. Then I wrote whatever came to my mind about the topic. I really hope I can write more frequently here this semester. My mind is full of projects and ideas for the future. See you in another post!