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Data Scientist Report 2018

Figure Eight’s Annual Data Scientist Report is now available. Figure Eight (formerly Crowdflower) has been taking the pulse of the data science community since 2015, and this year’s report focuses on both data scientists’ careers and compares their thoughts on AI with those of ethics professionals.

Data Scientist Report 2018

Figure Eight’s Annual Data Scientist Report is now available. Figure Eight (formerly Crowdflower) has been taking the pulse of the data science community since 2015, and this year’s report focuses on both data scientists’ careers and compares their thoughts on AI with those of ethics professionals. Some of the findings include: 89% of data scientists […]

The Time Has Come for Data Scientists’ Own GitHub

In this contributed article, email marketer and writer Adelina Benson discusses how data collaboration is the main weakness in the data science world, and, with many actively trying to improve the way in which data is shared, the future looks hopeful. The main issue facing companies in the industry is that there are only a finite amount of data scientists, and so the remit is not as broad as with a general social media site.

Gain In-demand Cloud, Data, and Machine Learning Skills with the Full Google Cloud Suite of Learning Programs on Coursera

Online learning leader Coursera now offers the full Google Cloud suite of programs on their learning platform. Learners can enroll in Google Cloud courses and Specializations to access top-quality cloud training. All courses include free hands-on labs to provide practical experience.

Data Scientists Will Change the World — Be One of Them

In this contributed article, Mamtha Parakh, Head of Data Science at Quartet Health, discusses what it means to be a mission-driven technologist, and how can we define and bring this culture to our own tech companies through four different approaches.

Infographic: The Data Scientist Shortage

Statistics point to a promising career in data science for anyone with the skills and interest to pursue this field in the 21st Century, whether one wishes to start from the first year of university or redirect his or her track midway. Given the current employment crisis featured in the infographic below, developed by our friends over at the University of California, Riverside, even individuals who have pursued programming and technical programs at high school could be thrust into more demanding positions in the work place.

Building a Winning Data Science Team

In this contributed article, Brad Cordova, co-founder and CTO of TrueMotion, discusses the importance of building a winning data science team, including actionable tips drawn from his own experience on structure, investment and building a culture where data science thrives.

How Operational Machine Learning is Transforming Industrial Operations

Our friends over at Falkonry just released the new infographic below “How Operational Machine Learning is Transforming Industrial Operations.” It includes some great data on how fast the industry is growing, who is using it (Toyota, Ciner, Honda, Kawasaki, etc.), how predictive analysis works, and applications per market (semiconductor, oil and gas, energy, automotive, mining, etc.).

Citizen Data Scientists – Are we there yet?

In this contributed article, Matthew Attwell, Risk & Client Services Director at The ai Corporation (ai), discusses the advent of the Citizen Data Scientist and how this designation is unfolding over time. Undoubtedly in the long term, solutions will become more flexible and dynamic to realize the full definition of the CDS. In the short term, however, we require data scientists to actively engage with and support the budding CDS within the business.

A Data Scientist’s Guide to Communicating Results

In this contributed article, technology writer and blogger Kayla Matthews discusses the field of data science is as unclear and vague as a muddy lake and it is critical to properly communicate results. While most terms and concepts include a legitimate definition, it’s all too easy to get bogged down in technical jargon. As such, some ideas mean different things from company to company and even — in some cases — from project to project.