

Intro to Data Science at UC Berkeley taught by Jeff Hammerbacher - rxin
http://datascienc.es/schedule/

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jhammerb
Hey,

We're on iteration 2 for this course, and it's still in somewhat rough shape.
If you plan to devote significant time to the lectures, I'd recommend waiting
until next spring, when we'll be teaching iteration 3 online at <http://ds-
class.org>.

Later, Jeff

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dhawalhs
Awesome! The URL seems similar to other Coursera courses. Will this course be
offered online through Coursera?

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demian
Maybie it's just me, but "Data Science" seems to be basically enterprise
information systems (ETL, dataflow diagrams, data mining, Data Warehousing,
business inteligence, and so on) but with a cool mobile-social-esque feel
associated to the term.

I had classes in information systems analysis & design with the exact same
content.

~~~
baconner
There's definitly been some ruffed feathers from the BI professionals and data
analysts over the "data scientist" title. We like this band before they were
popular man!

And there's some truth to the criticism that its mainly a rebranding. Someone
(can't recall the source, sorry) recently defined "data scientist" as "a data
analyst who lives in California."

That said even though many of the generalized tasks are the same I think
there's some value to the title. There are a broad range of big pro and
analyst roles that don't fit. Lots of big pros just make ssrs reports or just
build star schema or look at data for insights but don't apply any hypothesis,
test, repeat method.

The key differentiators for a data scientist IMO are

\- can do everything required to go from piles of unorganized data to usable
insights. From data munging to visualization design to programming to applying
statistics correctly to analyst activities like knowing what business
questions to ask

\- when doing analyst work they operate using scientific(ish) methods to test
and verify data hypotheses.

That describes many data analysts and BI pros that don't have cool titles now,
but may soon. Recognizing the difference between people and businesses that do
all of that vs report writers and ad hoc olap browsing users is valuable and
positive IMO.

~~~
demian
So, basically, you are saying that the main difference is that data scientists
also make desicions based on the data, while the BI/DA works as a "data guy"
for executives. Is that a correct way to put it?

In a way there seems to be a parallel between the enterprise programmer vs.
hacker, and the business inteligence/data analyst vs. data scientist.

~~~
baconner
Yeah or at least the execs are saying "getting more users is important. How
can we improve signups?" instead of "get me a time on signup page metric on
report x."

A data scientist is like an analyst that doesn't have to go beg the tech guys
to collect a new data set or build a new mining model, etc.

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mark_integerdsv
Lots of back and forth over the nomenclature as usual. I hope not to obfuscate
further by adding my definition.

I'm currently a BI consultant aspiring to the title of data scientist and
here's my motivation...

Traditional business intelligence skills basically refer to people who are 'IT
guys that have finance knowledge' ...so generally you'll find yourself doing
pretty general reporting along with some financial performance management
(FPM) albeit at the data modeling/ metadata modeling level (you're building
metadata models and cubes/reports dashboards with drill down not just flat
reports.) All of this is done at the whim of some exec/BA/line manager all of
whom (in my experience)seldom understand the subject well enough to actually
pose sensible strategic questions.

Data science implies several levels of creativity expressed through solid
technical skills along with a dash of journalism. Maybe it is just a
rebranding but what it represents to those in the field is a total paradigm
shift in terms of where and how the skills are applied. This is key because
all too often my work as a BI consultant boils down to churning out x number
of meaningless reports by a certain date so that some head of department can
get his bonus and justify the Oracle purchase that incidentally resulted in a
3 day trip to Paris funded by a stunningly sophisticated sales team.

If I come off cynical it's because I am passionate about data. I believe that
data science and the paradigm shift it represents has the power to really
change human lives and I believe that it has a key role to play in the future
of the evolution of our species.

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rxin
This year's offering has some changes from the Spring 2011 version of the
course (the assignments are all different), but you can view the Spring 2011
at <http://datascienc.es/spring-2011-course/>

~~~
noenzyme
Anyone know the password to watch to old videos?

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rxin
Try the course name, minus the "intro to", in one word.

~~~
_casperc
That would be "datascience", lower case.

~~~
big_data
Bummer. It appears we have been locked out from the videos.

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ahalan
Related: Data-Driven modeling course by Jake Hofman (Yahoo Research):
<http://jakehofman.com/ddm/recent-posts/>

lots of practical exercises, playing with real data and APIs

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Retem
I must say I am quite disappointed... watched 2 hours of this, then started
skimming, sorry but everything I have encountered is quite trivial (and I see
myself as a rookie in the field). Did other HNers find new bits in those
lectures? if so, please point out.

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conroy
I took this class last year (Spring 2011). Hammerbacher's a great professor.
He focuses on teaching real-world data analysis tools and skills.

~~~
demian
It does looks great. Especially the examples.

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swang
I'm confused since it looks like the course has already started. Can we still
submit old assignments for credit?

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ahalan
nice collection of resources: <http://datascienc.es/resources/>

