What's new in data science? Flip through this week's Top 5 to read a report on the most coveted skills for data scientists, top universities building AI labs, data science workstations for AI deployment, and more.

1. INSIGHTS AND INNOVATIONS
FOR BUSINESS LEADERS
APRIL 26, 2019
DATA SCIENCE
TOP 5

2. 2
THE RACE TO
STAY AHEAD WITH
DATA SCIENCE IS ON

3. 3
BUSINESS LEADERS HAVE TURNED TO
DATA SCIENCE TO CREATE
DIFFERENTIATED SERVICES AND GAIN
A COMPETITIVE ADVANTAGE.
SEE THIS WEEK’S TOP 5 HEADLINES
ON WHAT’S NEW IN DATA SCIENCE.

4. 4
DATA SCIENCE
TOP 5
#1
#2
#3
#4
#5
#1 MOST IN-DEMAND DATA SCIENCE SKILLS INCLUDE ML AND
PYTHON
#2 THREE LEADING UNIVERSITIES JOINED THE NVIDIA AI LABS
PROGRAM
#3 DATA SCIENCE WORKSTATIONS ARE TRANSFORMING AI
DEPLOYMENT
#4 END-TO-END DATA SCIENCE DRIVES BUSINESS DECISIONS AT
LINKEDIN
#5 DATA SCIENCE, THE FOURTH PILLAR OF THE SCIENTIFIC
METHOD

5. 5
MOST IN-DEMAND DATA SCIENCE SKILLS
INCLUDE ML AND PYTHON
SOURCE: https://searchbusinessanalytics.techtarget.com/feature/Most-in-demand-data-science-skills-include-ML-Python
#1
LEARN MORE
“As the role of data scientist grows in
magnitude, it's more important than ever
to stay current on today's most in-demand
data science skills. But it's not just the
programming and mathematical skills that
data scientists need to hone; domain and
business knowledge is equally valuable. ”
“The top tech skills employers look for most
in data scientists are machine learning and
expertise in Python, R, SQL and Hadoop,
according to research results published in
April 2019 by Indeed, one of the top jobs
sites.”

6. 6
THREE LEADING UNIVERSITIES JOINED THE
NVIDIA AI LABS PROGRAM
“NVIDIA is partnering with three leading
universities — Georgia Tech, the University
of California, Davis, and Texas A&M — as
part of our NVIDIA AI Labs program, to
build the future of graph analytics on
GPUs. NVIDIA’s work with these three new
NVAIL partners aims to ultimately create a
one-stop shop for customers to take
advantage of accelerated graph analytics
algorithms.”
SOURCE: https://news.developer.nvidia.com/graph-technology-leaders-combine-forces-to-advance-graph-analytics/?ncid=em-wee-n1-83901
#2
LEARN MORE

7. 7
DATA SCIENCE WORKSTATIONS ARE
TRANSFORMING AI DEPLOYMENT
With more data available than ever before
for data scientists, it’s crucial to have the
right software and hardware solutions to get
faster time to insight. The combination of
NVIDIA’s CUDA-X AI GPU-accelerated
software, including RAPIDS, and the new
NVIDIA-powered data science workstations
serve as an integrated hardware and
software solution for data science that
allows you to bypass traditional data center
setups to get faster performance and real-
world benefits.
SOURCE: https://info.nvidia.com/transforming-ai-development-data-science-workstation-reg-page.html
#3
LEARN MORE

8. 8
END-TO-END DATA SCIENCE DRIVES
BUSINESS DECISIONS AT LINKEDIN
SOURCE: https://twimlai.com/twiml-talk-256-end-to-end-data-science-to-drive-business-decisions-at-linkedin-with-burcu-baran/
#4
LEARN MORE
In this episode of This Week in Machine
Learning & AI, Burcu Baran, Senior Data
Scientist at LinkedIn, joined the podcast to
talk about each phase of the machine
learning production process, how her
“horizontal” team works with other more
“vertical” teams, best practices when
dealing with data partitioning at scale, and
more.

9. 9
DATA SCIENCE, THE FOURTH PILLAR OF
THE SCIENTIFIC METHOD
“NVIDIA CEO Jensen Huang revived a
decade-old debate last month when he
said that modern data science (AI plus
HPC) has become the fourth pillar of the
scientific method. While some disagree
with the notion that statistical analysis
alone can reveal undiscovered laws, the
argument may be moot if data science
continues its current course being an
extremely useful and in-demand tool for
all manners of scientific discovery.”
SOURCE: https://www.datanami.com/2019/04/15/is-data-science-the-fourth-pillar-of-the-scientific-method/
#5
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