►
Description
Date: 12/04/20
Presenter: Renata Rawlings-Goss
Institution: South Big Data Hub
Title: "2021 Opportunities for Data Science Education and Resources"
http://sbdh-prod.ideas.gatech.edu/resources/newsblog/education-and-workforce-working-group
A
B
Getting
applied
data
science
experience
a
lot
actually
in
the
kind
of
connecting
them
with
the
federal
sphere,
and
you
know
I
too
do
a
lot
of
thinking
and
also
empirical
work
on
kind
of
ethics
surrounding
data
science
and
ai,
and
that's,
I
think,
yeah
I
I
think,
like
I
see
a
few
others
I
came
in
late,
but
it
sounds
like
a
few.
Others
have
maybe
mentioned
that,
and
so
that's
something
that
I
would.
C
But
I've
also
been
working
with
a
group
of
younger
faculty
in
schools
of
public
affairs
putting
together
and
collaborating
on
resources
that
we
can
use
to
teach
in
our
classrooms.
And
that's
everything
from
you
know.
Basic
coding
to
you
know
artificial
intelligence
and
how
you
use
that
in
in
our
classrooms
and
for
applied
examples
in
our
setting.
So
we're
really
interested
in
our
need.
Is
you
know
how
do
we?
How
do
we
collaborate
around
these
resources?
C
Everything
from
you
know
syllabi
to
full
courses,
and
we
have
some
great
younger
faculty
who
are
developing
fully
open
courses
that
to
be
able
to
share
those
across
institutions,
maybe
to
be
even
to
be
able
to
share
faculty
members
and
students.
Sharing
courses
across
institutions
would
be
super
helpful
for
us,
as
well
as
supplied
projects
for
them
to
be
able
to
work
on
with,
under
the
guidance
of
those
who
have
more
expertise
than
maybe
our
our
faculty.
So
we
have
a
group
called
data
science
for
public
service
I'll
put
that
in
the
chat.
C
A
D
Yeah
so
cynthia
we
apparently
need.
We
definitely
need
to
talk
not
in
this
setting.
Apparently
so
I've
got
so
hi,
I'm
carl
schmidt.
I
used
to
be
at
vaporez
university,
where
I
started
their
data
science
undergraduate
program
was
running
their
analytics
and
modding
master's
degree.
This
year
this
semester,
I
moved
to
trinity
christian
college,
which
is
just
south
of
on
the
south
side
of
chicago
there.
D
I
got
hired
as
program
coordinator
for
making
a
data
analytics
program
there
and
starting
a
data,
hopefully
a
data
center
and
things
which
fitting
in
with
their
mission
and
everything
else,
part
of
the
reason.
I
say
that
this
data
science
for
social
good,
we're
hoping
really
to
deeply
integrate
into
what
we're
doing
curricular-wise
and
through
the
center
with
data
science
for
social
good
stuff.
The
other
reason
I
wanted
to
come
up
come
after
cynthia
was
because
cynthia
gave
me
a
perfect
opening
because
she
asked
how
can
we
share
this
stuff?
D
And
I
have
an
answer
for
you
and
in
fact
I
have
a
really
desperate
plea
answer
for
you.
So
I
am
also
a
member
of
the
acm
data
science
task
force,
which
is
in
the
pro.
So,
if
you
don't
know,
acm
acm
is
association
for
computing
machinery,
so
they're
one
they're,
they're
they're,
the
international
professional
society
for
computer
science,
people
lots
of
computer
science.
D
People
are
in
the
ieee
also,
but
acm
is
solely
computer
science
and
the
task
force
that
I'm
on
is
charged
with
putting
together
a
set
of
curricular
recommendations
for
computing
for
data
science,
undergraduates,
and
so
that's
we're
in
we're
working
and
releasing
draft
three
sometime.
This
spring
part
of
what
we
intend
we
intended
to
release
with
draft
three
was
examples
of
courses
that
people
are
using
and
teaching
data
science
stuff
in
and
how
that
maps
to
the
various
content
that
is
in
the
recommended
computing
skills.
D
So
any
of
you,
anyone
that
is
actually
teaching
a
class
or
has
content
or
has
people
that
are
teaching
classes
that
want
to
get
your
course
stuff
in
front
of
people.
This
is
a
great
way
to
do
it
because
when
it
gets
it,
but
basically
what
we're
looking
to
do
is
we
and
depending
upon
what
documents
you
read
some
yeah,
so
I
can
share
the
link
and
in
fact
I
put
the
link
to
the
the
task
force
web
page
on
on
the
ether
board.
D
I
just
put
in
the
chat,
so
the
the
most
recent
draft
is
on
that
task.
Force
page,
as
is
the
call
for
it,
do
not
be
frightened.
If
you
see
exemplar
courses
anywhere,
it
just
happens
to
be
the
language
that
sort
of
got
floated
around.
We
are
well
aware
that
the
data
science
courses
are
all
sort
of
in
flux.
We
want
examples
of
courses
and
any
examples
of
any
courses.
It
doesn't
matter
whether
they're
in
computer
science
or
not.
D
In
fact,
we
would
much
we'd
be
very
happy
to
have
a
bunch
of
courses
that
are
not
in
computer
science
that
people
have
spent
some
time
to
say.
Oh,
hey
we're
teaching
these
things
that
you
say
are
from
computer
science
in
these
other
courses,
because
what
we
want
to
be
doing
with
this
curriculum
is
really
helping
to
start
the
from
the
task
force
side.
Our
goal
is
to
really
start
the
conversation
about
what
broad
curricular,
documentation
or
curricular
guidelines
for
data
science
should
look
like.
The
task
force
is
very
intentionally
focusing
on.
D
Only
our
document
is
only
computing
things.
There
are
several
references
to
and
you
need
some
statistics
and
math
stuff,
but
we
are
not
putting
that
in
this
document
because
we
are
all
computer
science,
people
and
so
having
some
of
those.
Those
legions
to
other
places
is
totally
fine
and
our
hope
and
sort
of
I
will
say
we
are
getting
some
traction
in
starting
to
possibly
have
an
inner
professional
society
task
force.
D
That
will
create
a
general
curricular
guideline
for
undergraduate
data
science
curriculum,
but
that
has
been
very,
very
slow
going
because
it
has
been
really
hard
to
get
other
professional
societies
that
are
not
on
the
international
level
or
used
to
writing
extensive
curricular
guidelines
to
participate
and
and
step
up
and
say
yeah.
We
can
do
this
so
yeah
if
you
want
to
bug
your
asa
reps
or
your
maa,
reps
or
other
reps,
for
professional
societies
that
are
not
ieee
or
acm
by
all
means.
A
Yeah
now
this
is
a
great
thing,
because
then
we
can-
and
I
think
these
are
efforts.
We
definitely
want
to
look
at
too
with
the
professional
societies
and
taking
in
the
guidance
there's
a
couple
of
other
examples
of
this
that
they're
doing
something
similar
in
the
european
union
right
now,
as
well.
Around
data
science,
as
well
as
your
previous
national
academies
report,
around
recommendations
for
undergraduate
data
science.
A
We
can
put
those
links
too
so
yeah,
adding
it
thanks,
kendra
for
adding
them
to
the
to
the
ether
pad
as
well,
so
one
role
could
be
trying
to
connect.
You
know
if
people
are
on
these
calls
or
on
different
efforts
or
in
your
school's
efforts
to
try
to
connect
these
efforts
so
that
we
can,
you
know,
have
some
shared
some
shared
economies
of
scale,
maybe
around
some
of
the
things,
but
but
definitely
that
link
kendra,
just
added
it
to
the
ether
pad.
D
D
Anyone
that
has
courses
we
desperately
need
people
to
submit
example,
courses
because
we
are
just
not
people,
aren't
submitting
them
right
now,
and
so
we
really
want
to
include
those
courses,
so
anyone
that
wants
to
get
their
their
stuff
in
front
of
other
people.
People
will
read
these
and
and
frequently
what
happens
with
the
acm
curriculum
stuff.
Is
people
look
at
those
example
courses
and
then
we'll
reach
out
to
people
to
say?
Oh,
I
want
to
replicate
this
or
I
want
to
get
your
content.
E
A
F
This
is
a
10-week,
long
program
that
we
run
in
the
summer.
That
brings
students
in
from
a
variety
of
disciplines
and
has
them
work
with
several
of
our
data
scientists
on
projects
related
to
social
science,
human
services,
public
policy,
environment,
education,
urban
informatics.
So
last
year
we
had
a
project
on
using
data
science
to
detect
voter
suppression
and
vote
dilution
and
another
one
on
detecting
missing
disinformation
around
kobit,
so
that
that's
the
link
there
for
our
program
that
you
can
see.
I
also
put
it
in
the
ether
pad.
A
Yeah,
no
there's
two
things:
one.
We
should
have
a
discussion
about
team
team.
Science
is
one
of
our
new
focus
areas
for
for
the
south
around
trying
to
help
with
large
interdisciplinary
teams
of
scientists,
but
then
also
just
trying
to
talk
through
that
idea
of
the
students
also
have
a
interdisciplinary
flavor
to
them
too,
and
sarah
stone,
who
runs
that
program
is
actually
a
a
the
deputy
director
for
the
west
hub.
So
she
was
just
talking
to
us
about.
You
know
a
group
of
people
that
are
running
programs.
A
We
have
a
program
here
as
well
in
data
science,
for
social
good,
there's
one
in
chicago
there's
a
couple
in
other
places,
but
she's
forming
a
group
of
those
programs
to
try
and
look
at
best
practices
eventually.
So
sarah
might
be
a
good
person
to
talk
through
those
that
are
interested
in
data
science,
for
social
good.
That
group,
we're
hoping
to
you
know,
have
her
she's
leading
the
group,
but
to
also
get
recommendations
from
them
about
how
to
best
start
these
programs
and
how
what
they've
done
and
what
some
of
their
processes.
A
F
A
Yeah
she
was
talking
about
a
white
paper
that
might
put
out
as
well,
but
you
know
just
the
interaction
you
know
so
that
people
can
see
your
face
and
talk
to
her
directly
if
they,
if
you
want
to
get
in
touch
with
her
she's,
a
extremely
extremely
personal
and
a
good
and
good
person
to
know
as
well.
Okay,
so
let's
go
with
lenore!
You
want
to.
G
G
That's
that's
my
personal
interest,
I'm
also
here
with
my
hat
as
pi
of
the
tufts
tripods,
but
I'm
interested
in
pipelines
for
undergraduate
research,
undergraduate
mentoring
and
bringing
undergraduates
into
contact
with
data
science
as
it's
done
for
reals,
and
so
they
get
interested
in
going
on
for
graduate
education.
I
there's
been
so
much
about
social,
good
and
ethics.
G
I
should
do
you
guys
all
get
the
hdr
newsletter,
probably
not
so,
there's
a
there's,
a
project
that
we've
started
to
try
to
write
undergraduate
level
case
studies
in
ethics
that
came
out
of
actually
the
pi
meaning
that
renata
ran
some
of
the
discussions,
and
I
could
probably
put
the
link
on
into
chat
it's
open
to
everybody,
the
nice
thing
about
it.
It's
it's
not
a
very
ambitious
project,
but
with
a
couple
of
hours,
if
you
have
an
idea
for
a
data
science.
G
Ethics
case
study
we'd,
like
you
to
write
one
or
if
you
want
to
help
somebody
else
write
one
or
you
want
one
on
a
particular
topic.
There's
a
place,
it's
just
all
crowdsourced
in
a
google
doc
kind
of
like
the
ether
pad.
So
I
can
put
the
main
link
both
in
chat
and
in
the
ether
pad
in
case.
Anyone
is
interested
in
that
yeah
thanks
yeah,
that's
fantastic.
H
I'm
sorry
for
the
disruption
and
comings
and
goings
and
things
I'm
a
professor
at
amherst
college
and
I'm
particularly
interested
in
aspects
of
building
data
acumen
for
undergraduates,
ensuring
that's
really
done
in
a
way.
That's
diverse
and
inclusive,
and
also
building
connections
with
community
colleges.
E
Good
morning,
paul
donovan
at
the
university
of
pittsburgh
in
biology
and
focused
on
helping
faculty
become
more
comfortable
and
fluent
using
big
data
data
science
principles
and
practices
and
integrating
those
throughout
the
undergraduate
biology,
curriculum,
not
exclusive
to
collaborations
with
others.
But
there's
a
lot
of
work
to
be
done
in
in
biology.
Ecology
and
evolution
is
way
ahead
of
the
game
with
big
data
sets
bioinformatics.
Obviously,
but
we
run
a
project
called
cubes
which
essentially
allows
faculty
to
share
resources
and
collaborate
in
their
own
professional
development.
A
And
he's
being
modest,
cubes
has
done
a
lot,
a
huge
amount
in
faculty
development
and
they
have
a
platform.
You
know
so
just
putting
the
link
there
too
so
they've
helped
other
faculty
communities
to
engage
in
shared
course
work.
So
sam
is
downplaying,
but
they've
done
quite
a
bit
in
this
space
for
a
number
of
years.
That
is
that
some
is
translatable.
B
B
E
May
hi,
my
name
is
main
nguyen.
I
am
I'm
a
researcher
at
the
university
of
california,
san
diego,
so
I'm
pi
on
one
of
the
hdr
ideas
lab
project
to
build
a
knowledge-based
system
for
synthetic
biology,
but
I'm
also
teaching
a
course
in
a
new
data
science
undergraduate
at
ucsd
and
I'm
interested
to
hear
how
other
people
are
developing
their
curriculum
so
that
you
know
data
science
is
different
from
computer
science,
for
example,
so
be
interested
to
hear
that.
I
Hi
everyone.
First
of
all,
I
apologize
for
keeping
my
video
off
it's
just
unstable
today,
so
I
don't
mean
to
be
rude,
but
it's
nice
to
see
all
of
you.
I
am
a
faculty
member
up
at
st
catherine
university
up
here
in
saint
paul
minnesota,
and
we
just
recently
started
a
data
science,
undergraduate
curriculum,
and
so
I'm
here
mainly
just
to
really
hear
all
the
fabulous
ideas
and
ways
that
we
can
connect
and
and
looking
to
build.
E
E
J
I
J
Data
htc
with
a
domain
science,
I
put
a
link
in
the
chat
right
now.
It's
a
this
program
is
ending,
so
my
interest
in
this
co-working
group
is
first
stage.
I
think
I'm
scheduled
to
give
a
talking
networking
group
in
john.
I
want
to
share
my
experience
with
this.
How
big
data
can
can
be
because
we
all
know,
because
it's
useful
for
other
disciplines,
how
to
link
this
either
educational
research
perspective
work
with
other
disciplines.
J
My
interest
also
is
a
high
alert
on
the
curriculum.
What's
because
we
have
a
such
a
group
of
experts,
how
we
can
collectively
do
something
kind
of
back
to
the
community,
for
example
some
red
white
paper,
or
something
to
to
have
our
own
recommendation.
I
think,
what's
the
thing:
that's
someone
mentioned
the
task
force.
I
think
that's
a
very
good
way
to
go,
and
also
others
will
be
how?
J
K
Hi
good
morning,
everyone
thanks
renarta
for
organizing
this,
along
with
others.
So
my
name
is
waheed
bajwa,
I'm
a
faculty
at
rutgers
in
ece
and
statistics,
and
my
connections
to
hdr
are
that
I
have
a
joint
grant
with
two
collaborators,
one
of
whom
is
here
chris
tunnell,
and
in
terms
of
why
I
joined
this
group.
One
of
my
interests
is
that
I'm
quite
even
though
I'm
doing
a
lot
of
research,
I'm
quite
passionate
about
the
teaching
aspect,
especially
the
undergraduate
teaching.
K
So
I
wanted
to
introduce
something
for
undergraduate
students
accessible
to
all
engineering
majors,
as
long
as
they
had
taken
probability
and
linear
algebra,
and
some
of
the
things
that
we
have
been
doing
there
is
a
is
a
mix
of
like
under
helping
them
understand
the
fundamentals
from
both
at
least
some
mathematical
basis,
as
well
as
teaching
them.
How
much
to
trust
these
library
solutions
and
how
much
they
should
question
them.
K
K
They
have
already
been,
you
know
very
nicely
managed
in
kaggle
and-
and
you
know
so
so
that
is
one
of
the
challenges
that
we
always
face,
which
is
how
do
we
teach
them
those
kinds
of
things
I,
the
issue
of
ethics
came
up.
I
spent
at
least
one
to
two
lectures
on
ethics
telling
them.
You
know
you
have
to
understand
what
you
know.
The
results
can
only
be
as
good
as
the
kind
of
data
or
the
biases
that
go
into
creating
those
data
sets.
K
So
all
of
those
things,
so
I'm
hoping
you
know
from
this
working
group
that
perhaps
we
can
come
to
some
at
least
some
resources
where
I
can
overcome
some
of
these
challenges
and
you
know,
provide
students,
a
learning,
experience
that
that
is
really
reflective
of
the
real
world
and
not
you
know,
teach
them
every
concept
using,
let's
say
amnest
images
again
and
again
and
again
yeah.
So
that's
that's
my
story.
A
Oh,
thank
you
and
I
so
I
want
to
be
sure
that
we
can
get
get
everyone
in
and
that
we
still
have
a
little
bit
of
time.
You
know
at
the
end
to
just
talk
about
some
of
the
opportunities
going
forward,
so
we
will.
I
think
this
is
a
good
format
where
I
think
we're
going
to
do
this
again
or
at
least
have
people
discuss
what
they
want.
A
So
this
won't
be
the
last
time
as
well
to
get
it
and
and
if
you
also
want
to
put
some
things
in
the
ether
pad,
I
do
want
to
just
go
around
and
just
make
sure
that
people
know
you
know
where
you
are
and
where
you're
from
and
then
we
can
try
and
and
look
at
some
of
the
recurring
themes
that
have
come
up
around.
You
know
either
curriculum
or
social,
good
or
ethics.
A
So
these
other
things
that
we're
hearing
to
try
and
plus
one
those
in
the
ether
pad
as
well
that'll
it'll
stay
up
and
you
know
who
getting
connected
directly
through
the
email,
but
really
this
idea
of
maybe
doing
more
task
force,
because
I
think
the
one
thing
that
happens
and
we've
done
a
several
different
working
groups
is
that
people
will
find
each
other
on
one
call
and
they'll
pair
up.
But
then
you
know
on
subsequence
calls
it's.
You
know
it's
hard
to
know.
Who
else
is
interested
in
that
area?
A
Who
else
can
bring
resources
to
that
area?
So
sometimes
it's
nice
to
also
have
a
dedicated
space
that
people
know
who's
interested
in
what
and
there's
some
type
of
regularity
to
maybe
even
meet
so
that
it
can
grow
and
and
scale
in
some
cases
too,
but
that
email
so
that
people
if
people
want
to
connect
directly
to.
But
you
know,
as
you
try
to
scale
on
some
of
these
bigger
topics
you
know
like
curricula
or
other
things.
A
F
A
F
F
And
my
interest
in
education
is
sort
of
selfish,
it's
hard
to
find
people
trained
in
what
I
want
to
do.
So
I
teach
a
project-based
data
science
course
in
engineering.
It's
mainly
cs
and
ece
students
next
semester
on
the
short
term.
I'm
adapting
that
to
a
physics
course
I
was
originally
going
to
have
it
be
a
mix
of
engineering,
students
and
physics
ones,
but
the
pandemic
and
I've
had
to
improvise
I'm
very
interested
in
learning
how
people
bring
sort
of
experiential
data
science
courses
to
physical
sciences,
there's
many
considerations
educationally,
but
also
bureaucratically.
F
I
also
run
a
cyber
training
project.
That's
more
about
training
in
our
field,
but
but
really
my
long-term
plan
is
sort
of
ten
year.
Plan
is
just
to
integrate
data
better
into
the
physics
and
hopefully,
natural
sciences,
education,
because
we
stress
mathematical
ability
just
because
back
when
well
the
old
textbooks
that
sort
of
just
the
the
technical
skill
you
needed
to
do
things
and
we
haven't
really
updated
it
in
the
last
50
years.
A
A
E
Okay
or
the
other
friend,
I'm
a
sean
furrier
math
faculty
at
miracosta
college
in
san
diego
county,
and
we
are
sergeant
we're
working
on
starting
our
data
science
program
and
I'm
trying
to
get
our
cs
and
csit
faculty
together.
So
we
can
look
at.
I
think
we
have
all
the
pieces
we
just
need
to
meet
and
and
start
and
I'd
love
to
hear
from
people
who
have
established
programs
and
they
can
share
resources.
E
I'm
also
a
part
of
the
california
chancellor's
office
statistics
institute
and
we
have
been
organizing
professional
development
for
new
stat
teachers
across
like
across
the
state.
So
I'd
love
to
hear
your
pd
experiences
as
well,
and
thank
you
another
for
having
me
I've
been
trying
to
join
the
meetings
and
every
time
something
comes
up
and
I'm
we
are
on
the
other
side
of
the
country.
So
the
time
difference
is.
E
Yeah,
thank
you
renata
yeah,
my
name
is
donald
o'leary.
I
work
for
the
national
ecological
observatory
network
or
neon
on
the
education
and
engagement
team
nice
to
meet
you
all
at
neon.
We
know
that
many
educators
are
interested
in
using
our
data
sets
as
a
part
of
their
big
data
curriculum.
So
I'd
really
like
to
make
myself
available
to
the
community
happy
to
support
your
teaching.
I
am
an
educator
myself
and
I
have
a
pretty
deep
background
in
remote
sensing.
E
I
think
one
thing
that
ecology
has
imagined
for
a
long
time
is
that
it
is
separate
from
society
and
that
is
kind
of
socially
agnostic,
but
as
we
are
now
in
the
anthropocene,
that's
impossible
to
extract
ecology
from
society.
So
we
want
to
better
understand
how
to
make
that
pairing
and
how
that
becomes
apparent
in
our
data
sets
so
yeah
nice
to
meet
you
all.
Thanks,
renata.
E
D
Hi
steve
fancily
here
I'm
director
of
advanced
analytics
at
carnegie
learning
in
pittsburgh.
I'm
also
a
co-pi
of
an
hdr
frameworks
grant
called
the
learner
data
institute.
So
my
interest
is
sort
of
collecting
data
from
learning
and
training
environments
that
you
might
all
have
and
thinking
about
how
to
use
those
data
to
improve
learning
experiences.
Engineer,
improved
learning
experiences
that
sort
of
thing
so
happy
to
hear
more
about
what
everybody's
working
on.
A
Yeah
happy
to
hear
okay,
so
a
quick
pack
wait
if
cheryl
still
wants
to
do,
I'm
saving
the
home
team
for
last
the
the
hubs
as
well.
So
we
can
talk
briefly
together.
So
I
think
if
there's
somebody
that
I
missed,
please
alright
have
rm
and
cheryl,
and
then
I
think
we
might
have
gotten
everybody
okay,
so
real
quick!
So,
like
I
said
home
team,
so
we
have
some
people
from
the
other
hubs.
A
I
see
here
so
shannon
mccain,
who
is
the
deputy
director
for
the
south
hub
shannon's
right
there
at
unc,
florence
hudson
who's,
the
executive
director
for
the
midwest
hub
at
columbia
and
john
mcmullen
who's,
the
executive
director
for
the
midwest
hub?
I
mean
for
the
northeast
hub,
sorry
and
for
the
midwest.
A
We
all
have
a
lot
of
priority
areas,
but
I
just
wanted
to
talk
a
little
bit
about
some
of
the
opportunities
and
maybe
you
guys
can
talk
to
for
for
next
year,
they're,
just
through
the
hubs,
and
then
we
can
talk
about
some
of
the
recurring
topics.
We've
talked
about
for
the
actual
working
group
and
building
those
in.
So,
if
you
can,
you
know
self-select
things,
we've
heard
so
far.
A
You
know
biology
remote
sensing
and
other
things
like
that
and
the
opportunity
to
collaborate
you
know
even
as
far
as
curriculum,
but
also
into
teaching
or
into
as
shared
resources,
or
you
know,
building
building
things
together.
So
you
know
those
are
topics
that
you
know
as
we
can.
We
want
to
kick
off
if
people
are
interested
in
leading
task
force
or
putting
together
a
particular
topic
based
on
what
you've
heard
today,
you
can
put
that
in
the
ether
pad
and
we'll
try
next
year
to
reach.
A
We
want
to
reach
out
to
you
to
try
and
see
about
maybe
putting
together
these
task
force
so
that
we
can
do
more
work
together.
We
can
hear
about
what
each
other's
doing,
but
also
doing
you
know,
work
together
that
can
help
move,
move
everyone
forward
or
help
with
all
of
the
things
as
data
science
we
talk
about,
is
it's
halfway
through
becoming
a
profession.
A
profession
is
one
where
you
actually
have.
A
You
know
certified
bodies
to
be
able
to
certify
what
skills
and
for
what
pieces
and
how
we
practice
data
science
in
so
many
different
ways
that
it's
not
really
a
discipline.
It's
really
a
practice
like
practicing
medicine
or
practicing
law.
Each
case
is
different.
Each
use
case
is
different
and
the
skills
and
techniques
can
be
different,
and
so
in
that
same
way
it
may
you
know
we
want
to
have
that
same
variety
reflected
here
in
the
working
group.
So
for
us
for
the
south.
A
I
won't
do
the
presentation
because
it'll
take
too
long,
but
that
will
I'll
put
it
up
in
some
ways.
We
have
a
seed
grant
program.
This
is
across
all
of
the
hubs
where
we're
interested
in
having
promoting
work
that
shares
that
mission.
That
is
not
necessarily
fundamental
research
work,
but
work
that
really
helps
with
connecting
for
us,
where
we're
interested
in
how
those
connections
are
built,
people
taking
on
leadership
for
building
bridges,
around
data
science,
education
being
one
of
our
priority
areas,
particularly
in
the
south.
A
A
We
funded
some
this
this
year,
one
for
consortium
for
hbcus
in
data
science,
a
data
science,
hb
consortium,
some
that
deal
with
k-12
in
different
areas,
some
that
are
social,
good,
so
k-12
and
I
think
north
carolina
and
florida,
and
also
homelessness
data
in
delaware.
Delaware
is
part
of
our
southern
states.
We
always
have
to
remind
them
delaware,
to
texas,
and
so
these
are
the
types
of
things
that
we're
interested
in
people.
A
Then
all
the
universities
that
are
brought
together
are
have
a
train,
the
trainers
or
we
train
the
faculty
on
the
best,
the
research
best
practices
for
teaching
data
science,
and
so
that
is
actually
happening
now
right
now
for
the
current
cohort
this
these
next
two
days
have.
This
is
the
last
day
of
their
train,
the
trainers
and
then
the
next
year.
Those
faculty
teams
then
create
modules
or
courses
or
run
workshops
at
their
own
institution
as
part
of
the
end
of
the
program.
A
A
So
those
are
the
three
programs
that
are
you
know
wanted
to
talk
about.
You
can
also
see
them
on
the
site
that
are
available.
There
are
opportunities
for
faculty
to
work
with
government.
Now
we've
had
non-profits
and
industry
before
as
part
of
pep
fig,
but
this
year
is
going
to
be
homeland
security
and
doing
faculty
development
and
also
seed
grants.
So
I'd
love
to
see
you
know
some
of
these
ideas
that
we
have
some
mechanisms
to
move
forward
with
work,
so
we
have
a
minute,
but
so
john
and
florence
are
shannon.
H
Here
yeah
so
we're
very
similar
to
the
south
hub
that
renata
talked
about,
but
all
the
hubs
have
regional
differences
based
upon
the
needs
and
interests
of
our
communities,
and
so
in
the
midwest.
We
are
very
focused
on
capacity
building
and
train
the
trainer
kinds
of
activities
with
a
very
sharp
interest
on
small
institutions
under
resource
institutions.
So
tribal
colleges
and
universities,
community
colleges,
minority
serving
institutions
very
interested
in
working
with
those
folks
to
help
build
out
their
capacity
for
training,
students
and
and
overall
workforce
development.
G
Okay,
great
real,
quick,
some
in
the
northeast
summit
columbia
and
we
actually
launched
a
northeast
student
data
core
a
couple
of
months
ago
as
part
of
our
seed
fund
program
and
so
I'd
love
to
reach
out
to
the
people
that
are
in
the
northeast.
I
mean
I'd,
love
to
invite
you
all
and
that's
part
of
what
I
think
we
should
talk
about
is
how
we
can
leverage
each
other.
So
I
put
a
link
to
it
under
my
name
of
the
northeast
student
data
core
we
have.
G
Our
goal
is
to
build
an
inclusive
community
of
data
scientists,
starting
with
the
students.
So
we
have
a
content
and
pedagogy
team
and
we
have
ibm's
donated
their
open
data
science
for
all
curriculum
on
github.
We
found
some
at
berkeley
mit,
and
now
you
all
brought
some
up.
I
think
we
could
have
a
place
that
all
of
us
can
go
to.
G
If
they
haven't
been
in
it
before
and
then
an
outreach
team
that
will
find
teachers
and
learners
to
participate
in
the
program,
including
students
that
may
not
be
in
an
institution
and
don't
have
access
to
this
type
of
of
work,
and
then
they
also
are
going
to
work
with
industry
and
not
not
for
profits
and
municipal
governments
to
find
internships
for
the
students.
So
it's
like
a
whole
life
cycle
of
making
them
aware.
G
You
know:
students,
aware
of
data
science,
helping
them
get
started,
nurturing
them
and
creating
relationships
so
that
they're
used
to
having
this
very
inclusive
view.
As
we
talk
about
bias
and
ethics
and
data
science
that
they're
used
to
listening
to
each
other,
the
underserved
and
the
ones
that
have
been
involved
in
it.
So
I'd
love
to
make
that
the
n
is
can
go
national.
We
can
change
what
the
n
stands
for
the
national
student
data
core.
You
know.
Maybe
it's
something
we'd
all
want
to
do
together.
So
that's
that's
the
idea.
A
Yeah,
so
I
mean
I
think
we
can
feel
free.
One
thing
I
do
want
to
ask
is:
if
you
have
other
thoughts,
you
know
if
you
about
what
we
can
move
forward,
we're
going
to
really
take
your
suggestions
for
next
year
and
looking
at
task
force.
So
if
you're
out
you,
if
you're
interested
in
leading
a
certain
effort,
please
reach
out,
I
will
put
my
my
email
address
is
also
in
there,
but
I
will
also
put
in
the
ether
pad,
but
you
can
get
a
get
attached
to
what
we're
doing
through
our
newsletters.
A
A
So
this
is
the
last
one
for
2020
and
please
I'm
glad
that
everyone
was
able
to
join
again
have
a
good
rest
of
your
year.
We
will
send
the
same
time
in
january,
but
we're
gonna
start
collecting.
So
if
you
also
have
links
to
some
of
the
things
we've
talked
about,
if
you
can
put
them
in
the
chat,
kendra
has
been
moving
down
to
the
ether
pad
and
we'll
collect
them
with
the
other
ether
pads
that
have
happened
throughout
the
fall
to
look
at
what
resources.
A
Under
this
education
working
group
we'll
have
a
link
to
the
combined
resources
coming
up
in
the
fall,
so
if
you
add
them
in
we
will
we
will
keep
them
and
I
keep
moving
forward.
So,
thank
you,
everyone
does
anyone
and
we'll
see
you
next
year.
Hopefully
you
know
with
a
whole
new
brand
new
brand
new
crack
on
the
year,
so
2021
has
to
be
different
than
2020
right,
correct,
so
exactly
well.
Thank
you.
Bye.
It's
good
to
see
you
good
to
see
you.