|
Gain free and
expert-led
training in AMR
genomics and data
sharing
|
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|
|
Free online
training to
strengthen
your AMR
genomics
expertise!
|
Dear
Marco,
Antimicrobial Resistance and Genotype
Prediction:
Data Sharing
and Analysis
is our
free online
course led by
experts in
bacterial
genomics and
data analysis,
focusing on
how to use
relevant tools
and databases
for the
prediction of
antimicrobial
resistance
(AMR).
Starting
on 30
September 2024,
our educators
will guide you
through
everything you
need to learn
to confidently
predict AMR
using your own
data,
understand
effective
data-sharing,
and enhance
your expertise
in AMR
genomics.
The course
will run live
for
three-weeks,
during which
time you will
be able to
interact with
our educators
and other
learners
(through the
FutureLearn
platform), and
exchange ideas
and thinking
with peers
from across
the globe.
This
is an
excellent
opportunity
for early
career
researchers,
healthcare
professionals,
and public
health experts
to benefit
from free and
accessible
training in
AMR
prediction,
using
genotypic and
phenotypic
data, and the
latest
genomics tools
and
technologies.
Sign
up for a free
place on the
FutureLearn
website today,
and start
learning from
30 September.
|
|
|
Start
learning:
30 September 2024
Live period:
3 weeks
Weekly study
expectation:
5 hours
|
Conor
Meehan
Nottingham
Trent
University, UK
Jane
Hawkey
Monash University,
Australia
Kristy Horan
AusTrakka
platform,
Australia
|
Gain
a certificate
on successful
completion of
the course to
demonstrate
your learning
investment.
|
|
|
|
Free
online
training to
strengthen
your AMR
genomics
expertise!
|
Dear
Marco,
Antimicrobial Resistance
and Genotype
Prediction:
Data Sharing
and Analysis is our free online course led by experts in
bacterial
genomics and
data analysis,
focusing on
how to use
relevant tools
and databases
for the
prediction of
antimicrobial
resistance
(AMR).
Starting on 30 September 2024, our educators
will guide you
through
everything you
need to learn
to confidently
predict AMR
using your own
data,
understand
effective
data-sharing,
and enhance
your expertise
in AMR
genomics.
The
course will
run live for
three-weeks,
during which
time you will
be able to
interact with
our educators
and other
learners
(through the
FutureLearn
platform), and
exchange ideas
and thinking
with peers
from across
the globe.
This
is an
excellent
opportunity
for early
career
researchers,
healthcare
professionals,
and public
health experts
to benefit
from free and
accessible
training in
AMR
prediction,
using
genotypic and
phenotypic
data, and the
latest
genomics tools
and
technologies.
Sign
up for a free
place on the
FutureLearn
website today,
and start
learning from
30 September.
|
|
Start learning: 30 September 2024
Live period: 3 weeks
Weekly study expectation:
5
hours
|
Conor Meehan
Nottingham
Trent
University, UK
Jane
Hawkey
Monash
University,
Australia
Kristy
Horan
AusTrakka
platform,
Australia
|
Gain
a certificate
on successful
completion of
the course to
demonstrate
your learning
investment.
|
|
|
|
Watch the course
trailer to
discover more
about what you
will learn
with our
expert
educators
|
|
|
- Explain the
genotypic
basis of AMR.
- Contrast and
critique the
various ways
to predict AMR
from linked
genotype
and/or
phenotype
data.
- Discuss the various
AMR databases,
and their
related
benefits and
limitations.
- Explain how
different AMR
prediction
tools can be
applied, as
well as how
their outputs
are
interpreted
and
implemented.
- Explain the current
limitations of
AMR prediction
tools.
- Describe the
process
required to
create and
share FAIR and
open AMR data.
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Other learning and
training
events that
may interest
you
|
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|
|
Other
learning and
training
events that
may interest
you
|
|
|
Image credit:
Colour
photography by
Ben McDade for
Connecting
Science
Wellcome Connecting
Science
Wellcome Genome
Campus,
Hinxton,
Cambridge,
CB10 1SA, UK
Genome Research
Limited, a
charity
registered in
England with
number 1021457
and a company
registered in
England with
number
2742969, whose
registered
office is 215
Euston Road,
London, NW1
2BE.
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