From the course: LinkedIn Learning Highlights: Data Science and Analytics
What’s in our data-driven future?
From the course: LinkedIn Learning Highlights: Data Science and Analytics
What’s in our data-driven future?
(upbeat digital music) - Current estimates suggest that over 50 billion things will be connected to the internet by 2020. We are now connected species. Humans connected to humans, humans to machines and machines to machines. But, we're still just at the very beginning as almost four billion people are still not connected to the internet. The real promise of the connected planet has yet to be realized. It will happen in the fourth industrial revolution. (digital whooshing) - I'm actually very comfortable saying that the cities in the future are connected and here's an easy example of this. When you go to take a train now or a bus, you expect to be able to say, hey, the bus is just two minutes away. You don't actually have to keep saying, oh am I late or did the bus already pass? Those things, you just know, 'cause you know exactly where the bus is and it improves ridership. It improves people's quality of service on there. More of that as that starts to take place is going to change how we think about the quality of life on not the crazy bold problems that are out there. But, many of the things that we take for granted. - As we look at the big areas that Quantum will have an impact in, problems in chemistry or material science where you need a level of accuracy and understanding the molecule and you can't get that accuracy with classical compute. So, where the computation would take you more than what was feasible, so we're looking at problems that might take longer than the lifetime of the universe even seconds or hours on the Quantum computer. - What makes blockchain technology so compelling is that it has broad disruptive applications. We've already seen many potential uses in several industries. One of the most exciting and promising opportunities is identity management. It's an important societal, political, economic and computer science issue. But, a foolproof method of proving one's identity has been an illusive goal. I'm encouraged by what I see with blockchain-based identity management. System developers and designers need to seriously consider how to experiment with some of these solutions now.
Contents
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Teaming up for data science2m 34s
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Exploring data ethics and privacy2m 22s
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Using Microsoft Excel as an analytics tool3m 9s
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Using statistics for data science2m 7s
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Working with data analytics platforms and tools3m 16s
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Helping others visualize data2m 39s
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Developing AI, machine learning, and natural language processing3m 12s
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Exploring deep learning, neural networks, and computer vision3m 5s
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Working with Python2m 45s
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Working with R2m 59s
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Working with SQL2m 27s
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Exploring data engineering3m 10s
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Exploring business intelligence and Power BI2m 59s
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Exploring business analytics and financial technology3m 12s
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What’s in our data-driven future?2m 25s
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