Beginner courses on machine learning

Sept. 24, 2019

Disclaimer: This is just my take on a couple of beginner courses offered on ML, not an expert. If you see any typos or errors in my post, feel free to comment.

For the last couple of weeks I’ve been hitting it balls deep on a Python data analysis course: that’s offered for free by HY (Helsinki University). I’ve just finished week 1 and had probably spent about 30 hours total doing these exercises. Mind you I’m not going for any credits on this course so I’m doing this on my own pace. So far this course has been amazing for number of reasons.

Weeks 1 and 2 focus on the Python fundamentals. Week 1 I feel has mostly been about lists and getting used to the different functions Python has built-in for easily manipulating lists and values. Now I’m heading out for week 2 and it seems to be on the same lines as week 1 except maybe more intermediate stuff compared to the first week.

I’m really not doing this course to grasp the fundamentals on Python, much better courses for that. I’m just waiting for the latter weeks so I can get into some basic machine learning and statistical analysis subjects. My goal during the next year is to grasp a solid fundamental understanding of machine learning.

In the past I’ve done the beginning of Andrew Ng’s Stanford course on ( and grasped some information on the basic techniques such as the cost function, linear regression, gradient descent and the manipulation of vectors and matrices in practice. At the moment my take on machine learning is that it’s just automated statistics. Someone can change my mind on this, but machine learning and AI is pretty far from the Terminator-esque utopia that most of the society seems to think it as.

Although Andrew Ng’s course has been touted by everyone as the starting point for starting to learn ML, I’ve decided to run through this data analysis course first and after that delve into the Andrew Ng -course. There’s quite a bit of differences although botch courses cover the same subjects and have a lot of overlap.

There’s also a website called that seems to also offer machine learning and statistics related curriculum but I haven’t yet checked this out, from what I know, most of the material there is behind a subscription wall, so there’s that. Anyway here are the 2 courses I’ve mentioned in this post and from my limited knowledge and experience in the subject I can really recommend either one of them for someone who wants to dig into machine learning:

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