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Top tips for your data science CV

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In order to get your resume to stand out amongst the stack, there are a lot of things to consider. Even simple choices like what font to use, should you use bold and italics to set off your subheads, job titles, and other features?

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10 of the most in demand jobs in Artificial Intelligence

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A recent Indeed report published really highlighted the talent gap within AI and machine learning with job postings are soaring butbthe number of searches is dropping. The report indicates that the drop is attributed to the lack of qualified professionals that are able to fill these roles.

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AI in Action Berlin Meetup June Recap

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The eighth AI in Action Berlin meetup took over Blacklane as we were introduced to the myth behind the Superman Data Scientist, Deep Learning for Computer Vision and developing a production-ready system from another top line up of Germany's finest AI and Data Science minds.

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AI in Action E26: Sotir Hristev, Head of Data Science at Exactag

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Head of Data Science at Exactag Sotir Hristev discusses the Data Science scene within digital marketing in Germany, how changes and the setup in organisations have an impact on the career path of Data Scientist, building an effective Data Science team in your organisation and more

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AI Mentors E15: Alex Siegman, AI Technical Program Manager at Dow Jones

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Alex Siegman, AI Technical Program Manager at Dow Jones on moving from Artificial Narrow Intelligence into Artificial General Intelligence, how Dow Jones are leveraging AI within their organisation, advice on how to forge a career in AI and Data Science, what a great Data Scientist looks like & more

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4 Programming Languages Every Big Data Enthusiast Should Embrace

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There are hundreds of programming languages, each one with their own set of features and uses., but for a data professional to be a success they will probably need to become familiar with more than one of these languages. Is it better to be a jack of all trades or master of one?

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Repairing the Plumbing of Data-Science

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With a lack of clear understanding regarding the purpose of a data scientist, some companies automatically assume a data scientist is a one-size-fits-all solution, but a more efficient option than investing in a data engineer as well.

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