Thanks for putting these resources together, this is amazing
Show HN: An Open-Source Data Science Curriculum
11–20 of 44 posts
Re: Show HN: An Open-Source Data Science Curriculum
#12I feel like lists of resources are OK, but with something like data science, which has its own branches and specialities, it would be good to have some kind of stack ranking of topics and information beyond just 'start here'. That way, a reader gets more and more conversant with the different ideas being thrown around.
Also, I don't have a list of these handy, but I've found long annotated notebooks/blog posts of worked data science examples very helpful for refreshing my memory on applied techniques. http://derandomized.com/ is a great example, maybe other HN readers have some favourites we could add.
Re: Show HN: An Open-Source Data Science Curriculum
#13I do a lot of statistical work, but wouldn't call myself a data scientist. To that end:
> I geared the original curriculum toward Python tools and resources, so I've explicitly marked when resources use other tools to teach conceptual material (like R)
Why did you choose Python over R? Personal preference, a bent toward Python in the online courses you found, or is Python generally considered the de facto language choice for professional data scientists?
I imagine you could tackle these courses with any programming language, but if Python seems to be the way the data science community is going, it would be helpful to know that. Personally, I'm curious because I'm trying to decide if I should pick up Python on the side to supplement the knowledge I already have of R and various other programming languages.
Also, thanks for putting all this together. It's great!
Re: Show HN: An Open-Source Data Science Curriculum
#14I'm biased as a non-technical analyst with an academic history, but I'm concerned that the curriculum doesn't meet the most basic needs.
Quoting the section 'An Academic Shortfall': "Academic credentials are important but not necessary for high-quality data science. The core aptitudes – curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature – that distinguish the best data scientists are widely distributed throughout the population."
In my estimation, none of those aptitudes are covered by teaching technical skills like databases, NLP, ML, graphical models, and the other topics this curriculum covers.
The "core aptitudes" generally boil down to asking the correct questions, establishing the correct answers, and correctly defending them. Academia doesn't automatically instill these skills, but it can do a great job of doing so.
Either way, inside or outside the ivory tower, an ace programmer who masters NLP, ML, Hadoop, and everything else could easily still come out without the required core aptitudes, and be thoroughly unprepared to do what data scientists are really expected to do: answer questions.
Re: Show HN: An Open-Source Data Science Curriculum
#15On the entry "NLP with Python O'Reilly / Book", note that a second edition might be "in the works." There is an online edition of the work in progress (updating for Python 3 and NLTK 3) available here [1].
[1] -- http://nltk.org/book3/
Re: Show HN: An Open-Source Data Science Curriculum
#16YES I support this.
Re: Show HN: An Open-Source Data Science Curriculum
#17I do a lot of statistical work, but wouldn't call myself a data scientist. To that end: > I geared the original curriculum toward Python tools and resources, so I've explicitly marked when resources use other tools to teach conceptual material (like R) Why did you choose Python over R? Personal preference, a bent toward Python in the online courses you found, or is Python generally considered the de facto language ch…
Apparently the R people realize Python over R already..
http://www.r-bloggers.com/the-homogenization-of-scientific-c...
Re: Show HN: An Open-Source Data Science Curriculum
#18I'm biased as a non-technical analyst with an academic history, but I'm concerned that the curriculum doesn't meet the most basic needs. Quoting the section 'An Academic Shortfall': "Academic credentials are important but not necessary for high-quality data science. The core aptitudes – curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature – that distinguish the be…
It's an open source curriculum, so you could get involved and help mold it to meet what you see are its needs as a curriculum, no? I'm not sure what I think of it yet as a curriculum, but I am bookmarking it and plan to come back to it for more resources. Personally, I think it's an interesting idea and something I want to watch to see how it unfolds.
Re: Show HN: An Open-Source Data Science Curriculum
#19I do a lot of statistical work, but wouldn't call myself a data scientist. To that end: > I geared the original curriculum toward Python tools and resources, so I've explicitly marked when resources use other tools to teach conceptual material (like R) Why did you choose Python over R? Personal preference, a bent toward Python in the online courses you found, or is Python generally considered the de facto language ch…
In most tech companies, data scientists have adopted python over R or Matlab. The benefit is it's easier to scale python to larger datasets, and of course easier for the engineers in the company to take python code that computes algorithms and such and put them into production / products.
Re: Show HN: An Open-Source Data Science Curriculum
#20Earlier quoted context omitted.
The assignments are, in fact, available: https://class.coursera.org/datasci-001/assignment You'll be required to login is all.
I'm logged in but get "Looks like you are not enrolled in this course!".
Google around, often times people have downloaded the lecture videos / homework assignments