The Python for Everybody course was great. I was excited to complete it (well, the first 3 courses in the roadmap): https://www.coursera.org/specializations/python As a non-programmer but a decent mather, I thought it presented the materials in a way that was easy to understand. In my mid-thirties now, I feel like I could have handled this at 18 just fine--but not in a patronizing way. It was just very clear and the…
As someone who has been both 18 and 30, 18 is a much easier time to learn a programming language.
Scott Page's Model Thinking course: https://www.coursera.org/learn/model-thinking . Broad overview of how to think in models to understand the world around you.
What does that mean to think in models?
Think scientifically/mathematically. It what most people who hang out HN do intuitively, but most of the general public does not. (Like how Dr Fauci talks about COVID-19 vs how Donald Trump does).
I second the recommendation for "Automata Theory", the explanations are crystal clear and I learned a lot.
I found the first part, on regular expressions really excellent (though the accelerated pace made it difficult to fully grasp all the proofs). He's a still-enthused expert. However, he didn't seem as passionate on the second part, decision languages. It's also a lot harder, yet is squeezed into even less time. To help you assess my observation: I scored in the highest segment (IIRC 95%)... After taking the course, I…
Your experience aligns with how most people feel about learning about Decision Languages, based on my experience in that class in college.
You can get a sample out of her Google talk on YouTube. Basically the course tells you ideas about how to read/manage time to learn things more efficiently.
And most importantly, why you should study and manage your time in certain ways. A lot of things in that course feels like it fairly obvious when you hear it, but often you might not have thought in those directions, and often it helps to get those things spelled out. If I had had that course in my early teens that would have helped me a lot.
I really enjoyed the part about recollecting vs rereading. This changed my perspective on how to read things. I have noticed I read less nonsense and retain more of the important topics. Also tried it with software docs. Although recollecting API names didnt help me make better software decisions but it came in handy while writing code. A bit of fluency helped reduce friction since I could code with less context switches.
I have no idea how 'Machine Learning' from Ng is not mentioned. It's fine in teaching you introductory (although it seems to cover more basics than a lot of other courses do, somehow) ML. But more importantly, it's a well designed course. You can see how each piece uses previous pieces and how it solves problems and edge cases not covered earlier.
This was the first course I did on Coursera and it is by far the best introductary course for machine learning I have ever seen, but my sample size is pretty small ;)
I quite enjoyed https://www.udacity.com/course/design-of-computer-programs--... -- program design by Peter Norvig. (Disclaimer: I had a very small part in preparing it.)
+1 for this. It's quite python-specific, but I found it amazingly insightful.
Programming Languages, Dan Grossman, UW. https://www.coursera.org/learn/programming-languages It is a 3 part course and a bit more intensive than other courses on Coursera with challenging assignments. It helped me gain a deeper understanding of statically vs dynamically typed languages. Designing a tiny language in Part B is the best part of the course. Concludes with a nice comparison between OOP and functional lan…
Did that too and it totally changed how understand programming (was a newbie back then).
That's not the entire explanation for Ng's use of Octave though. At the birth of Coursera in 2012, R and Python were already clearly established in the field of data science. R was the dominant open-source language for data science, with Python very close behind (and already gaining ascendancy among folks who identified with "machine learning" rather than "data science"). I remember Matlab/Octave being more associate…
I think his choice of Octave was really just to avoid using Matlab. I had taken several other courses around the same time, and they all used Matlab. All of the courses had arranged for a free Matlab license for the time the course was active. You also were given the option of buying the Student version for $99. That didn't last long, I haven't seen any courses offering a free license (or even using Matlab for that m…
I've taken 3 MATLAB courses on Coursera this year and they've all included free student access to MATLAB online. Also, a home use license for MATLAB is available for $149.
And most importantly, why you should study and manage your time in certain ways. A lot of things in that course feels like it fairly obvious when you hear it, but often you might not have thought in those directions, and often it helps to get those things spelled out. If I had had that course in my early teens that would have helped me a lot.
I really enjoyed the part about recollecting vs rereading. This changed my perspective on how to read things. I have noticed I read less nonsense and retain more of the important topics. Also tried it with software docs. Although recollecting API names didnt help me make better software decisions but it came in handy while writing code. A bit of fluency helped reduce friction since I could code with less context swit…
Ah yes, that is an important part. I certainly often fell into the trap of looking at the material, feeling it was comfortingly familiar and thus believed that I knew it. And then of course struggled to recall it when I needed it.