NVIDIA Introduces Five New Free Technical Courses for Developers

With
the
rapid
pace
of
technological
innovation
driven
by
artificial
intelligence
(AI),
keeping
skills
up
to
date
is
crucial
for
developers.
The
NVIDIA
Developer
Program
is
now
offering
five
new
free
technical
courses,
designed
to
provide
training
and
resources
essential
for
success
in
various
industries,
according
to
the

NVIDIA
Technical
Blog.

Accelerating
End-to-End
Data
Science
Workflows

This
course
enables
developers
to
build
and
execute
end-to-end
GPU-accelerated
data
science
workflows.
Utilizing
RAPIDS
accelerated
data
science
libraries,
participants
will
learn
to
apply
GPU-accelerated
machine
learning
algorithms
and
logistic
regression
for
large-scale
data
analysis.

• Implement
  GPU-accelerated
  data
  preparation
  and
  feature
  extraction
  using
  cuDF
  and
  Apache
  Arrow
  data
  frames.
• Apply
  GPU-accelerated
  machine
  learning
  tasks
  using
  XGBoost
  and
  cuML
  algorithms.
• Execute
  GPU-accelerated
  graph
  analysis
  with
  cuGraph.
• Build
  data
  visualizations
  with
  cuXFilter.

RAPIDS
Accelerator
for
Apache
Spark

This
course
focuses
on
leveraging
NVIDIA
GPUs
with
Apache
Spark
to
accelerate
workloads
and
reduce
costs.

• Use
  Apache
  Spark
  and
  integrate
  RAPIDS
  Accelerator.
• Run
  Spark
  CPU
  and
  GPU
  workloads
  to
  analyze
  performance
  gains.
• Utilize
  the
  RAPIDS
  Accelerator
  toolset
  for
  job
  tuning
  and
  speed
  estimation.

Introduction
to
Transformer-Based
Natural
Language
Processing

Transformers
are
fundamental
to
large
language
models
(LLMs).
This
course
covers
their
use
in
natural
language
processing
(NLP)
tasks
such
as
text
classification,
named-entity
recognition
(NER),
and
question-answering.

• Explain
  transformers
  and
  their
  role
  in
  LLMs
  for
  NLP.
• Analyze
  and
  generate
  text-based
  data
  using
  transformers.
• Leverage
  pretrained
  LLMs
  for
  various
  NLP
  tasks.

Prompt
Engineering
with
Llama
2

Participants
will
learn
to
interact
with
and
prompt
engineer
Llama
2
models
to
analyze
documents
and
generate
text.

• Write
  precise
  prompts
  to
  align
  LLM
  behavior
  with
  intentions.
• Guide
  LLMs
  with
  prompt
  engineering
  techniques.
• Create
  chatbot
  behavior
  by
  incorporating
  prompt-response
  history.

Synthetic
Data
Generation
for
Training
Computer
Vision
Models

This
course
uses
Omniverse
Replicator
for
synthetic
data
generation
(SDG)
to
train
computer
vision
models.

• Write
  and
  perfect
  Replicator
  scripts
  in
  Omniverse.
• Fine-tune
  pretrained
  models
  for
  object
  detection
  using
  PyTorch.
• Export
  trained
  models
  to
  NVIDIA
  Triton
  Inference
  Server
  for
  testing.

The
NVIDIA
Developer
Program
provides
developers
with
access
to
GPU-accelerated
servers
in
the
cloud,
offering
practical
expertise
through
a
blend
of
self-paced
online
courses
and
instructor-led
workshops.
The
program
also
includes
free
access
to
advanced
tools,
software,
and
a
dedicated
community,
enabling
developers
to
keep
pace
with
technological
advancements
in
accelerated
computing.

Community,
Software
Access,
and
More
Benefits

The
NVIDIA
Developer
Program
supports
technical
practitioners
with
resources
and
community
engagement
at
every
stage
of
their
journey
with
NVIDIA
technologies.
Benefits
include:

• Access
  to
  NVIDIA
  software,
  SDKs,
  APIs,
  libraries,
  and
  models.
• Use
  of
  GPU-optimized
  software
  and
  containerized
  apps
  from
  NVIDIA
  NGC.
• Personalized
  news
  updates
  on
  technological
  innovations.
• Participation
  in
  early
  access
  programs
  for
  new
  NVIDIA
  technology.
• Training
  options
  through
  NVIDIA
  Training
  and
  certification
  opportunities.
• Community
  engagement
  through
  NVIDIA
  Developer
  forums
  and
  events.
• Access
  to
  research
  papers,
  technical
  documentation,
  blog
  posts,
  and
  industry-specific
  resources.

Developers
are
encouraged
to
join
the

NVIDIA
Developer
Program
to
begin
accessing
these
resources
and
connecting
with
experts
and
peers
in
the
field.

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source:
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