
General Assembly's Data Science Course - Jasamba
https://github.com/justmarkham/DAT8
======
dataschool
Hi all! I'm the owner of the GitHub repo linked above. It's called "DAT8"
because it was the 8th session of General Assembly's part-time Data Science
course in Washington, DC.

Here's a bit of history, if you're interested:

\- General Assembly launched a standardized Data Science course curriculum in
mid-2013. The course used lots of slides, and taught both Python and R.

\- Over time, the curriculum evolved in different directions as instructors
around the world made their own modifications, both in terms of what was
taught and how it was taught. By early 2015, I think all instructors had moved
to teaching Python only.

\- I taught the course five times starting in mid-2014. Over the course of
those five sessions, I rewrote nearly all of the lessons and converted most of
them to IPython/Jupyter notebooks. I would estimate that 95% of the material
in the DAT8 repo is my original lessons.

\- Earlier this year (2016), General Assembly rewrote and relaunched a
standardized Data Science course curriculum. Therefore, if you take this
course in the future, I would expect that you will be learning from that new
curriculum.

For what it's worth, I wrote a 4000-word essay [1] about data science
education after teaching the course the first time.

I'm happy to answer any questions!

[1] [http://www.dataschool.io/teaching-data-
science/](http://www.dataschool.io/teaching-data-science/)

~~~
wwweston
Really appreciate your comments here. And your essay (and the larger
dataschool.io site), too. GA's data science class is one of several that I'm
considering signing up for -- and I'm also considering applying to be an
instructor. I think it's really promising that GA has instructors like you
that seem to have both the interest in and latitude to make the course as
enriching an experience as possible.

If you'd be open to answering some questions about your experience as an
instructor, there's a few other things I'm curious about:

\- What were your students like? Were they all qualified to be there? Were
there challenges dealing with outliers (either overqualified or under)?

\- What surprised or stretched you about your experience teaching at GA?

\- What background did you bring to it before teaching there?

If you'd rather answer privately, email's in my profile.

------
JPKab
I attended the first GA Data Science course to be offered in the DC area in
the spring of 2014.

Back then, the course was 3 months long, two nights a week, from 7PM to 10PM
on Tuesday and Thursday nights. The first part was all R, and the second part
was all Python (Scikit learn, etc).

I got a lot out of it, but it was a TON of work. Outside of class, I was
spending 2 - 3 hours a night doing homework. The teacher was great, and he
made extensive use of Git for all assignments. Homework was submitted via
commits to a class repo.

Other students who came into the course got less out of it, mainly because
they didn't have ANY background in programming, or because they simply didn't
put in the work.

Overall, I think it was awesome for me, but it's like anything else: You get
out of it what you put into it.

Edit:

I just noticed the repo was created by Kevin Markham! He was in my class, and
the dude is friggin brilliant!

~~~
dataschool
JPKab/John! Hilarious to cross paths with you again in the Hacker News
comments :)

Your compliment is appreciated, but you are way too generous!

So, after taking the first session of the course in DC (internally called
"DAT1"), I was a TA for DAT2, the co-instructor for DAT3 and DAT4 and DAT5,
and the solo instructor for DAT7 and DAT8. The repo linked above was my repo
for DAT8.

The curriculum evolved quite a bit since you took the course. One major change
is that by DAT3, we had moved to Python only. We had an increasing number of
students without a programming background, which was one of the reasons for
the shift to a one-language course.

And I totally agree: Students get out of it what they put into it.

------
elliottcarlson
I work at General Assembly as an Engineering Manager - check out our listing
in the Who's Hiring thread for onsite and remote engineering positions, but
also for teaching opportunities at our various campuses, and plenty of other
roles.

------
watty
Looks amazing but I doubt I could follow the curriculum without some class
videos and feedback on homework/projects.

Unfortunately they don't teach in my area and the online courses are much
higher level.

~~~
tibbon
Former GA instructor here.

I kept a LOT of stuff (~300 repos) on Github for student assignments when I
taught WDI, all public. I liked keeping it public by default, and advocated
internally for such for a few reasons; I didn't think there was anything much
in the repos that needed to be kept private, and I liked student's
contributions via PRs for turning in assignments to be public so that they
could show a strong history of doing stuff on github to future employers. I'm
also a huge FOSS advocate, and like pushing for things to be public when
possible as a default.

Some of the assignments could in theory be externally consumed, but I put
exactly zero time into making it more usable for people not actually in the
class.

------
ybrah
This seems pretty cool! I've been looking for something like this. I really
enjoy the open source courses on github, because I can do them at my own pace
and figure things out.

~~~
dataschool
ybrah: Great! I tried to write the IPython notebooks so that they could be
understood without too much further explanation. As well, all of the exercises
and homeworks have provided solutions. Feel free to let me know if you have
any questions.

------
jpitz
Can anyone who attended the course comment on the quality? This looks very
promising to me.

~~~
msellout
I wrote and taught GA's first data science curriculum [0], back when they were
a coworking space in NYC. I'm proud to say that out of 20 students, about half
got promotions, new jobs, raised significant capital, or had successful
acquisitions. Whether the course was a causal factor... it appears to have
been correlated.

Students who didn't have time to do much homework quickly lost interest in the
course. I wasn't experienced enough at teaching to handle this. I've become a
much better instructor since that first time -- at designing curricula,
lecturing, managing a diverse classroom, etc. So, I'd say the quality of the
class will be highly instructor-dependent.

[0] [http://selik.org/2012/07/04/teaching-data-
science/](http://selik.org/2012/07/04/teaching-data-science/)

