By Cecile Alper-Leroux Smart technologies powered by machine learning, natural language processing, augmented intelligence and distributed data collection interfaces are poised to transform the workplace and the world of HR leaders. In this blog post, you will learn about the potential virtues of ambient HR and virtual reality experiences for the future of work. Read on to decide if HR is ready. Note that, regardless of the technology, putting people first is a must. Employees today want it all… and so do their employers!

If you were a data scientist three years ago, you could pretty much write your own ticket. Everybody in the industry, it seemed, either wanted to hire a data scientist, or wanted to be one. But today, thanks to a confluence of factors, organizations are beginning to question whether they need these digital unicorns at all. The key to understanding the dynamic at play here is to separate the activity of "data science" from the persona of "data scientists." Organizations most definitely want to do data science to get insight from their data.

In case you missed them, here are some articles from July of particular interest to R users. A tutorial on using the rsparkling package to apply H20's algorithms to data in HDInsight. Several exercises to learn parallel programming with the foreach package. SQL Server 2017, with many new R-related capabilities, is nearing release. Ali Zaidi on using neural embeddings with R and Spark to analyze Github comments.

Python is a new language for me and I've learnt it (reasonably) only for trying out AI...I ve strong base in Math and stuff.. so python is the only thing keeping me from going ahead with AI...I learnt python from " Learn Python the hard way" by zed Shaw...And comfortable with that is taught in the book...loops, Functions, classes, lists etc...Now my confusion is what to do next...Shud I continue learning python and try AI only after mastering python...Or shall I go ahead with AI and develop my python skills as I go along... I've decided to take AI course from edx by ColombiaX....It's based on Python.. Any suggestions (or resources) will be very helpful...Thanx in advance

The course is a new one by Andrew Ng, Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/Google Brain. It will start Aug 15. About this course: If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.

Artificial intelligence is transforming our lives at home and at work. At home, you may be one of the 1.8 million people who use Amazon's Alexa to control the lights, unlock your car, and receive the latest stock quotes for the companies in your portfolio. In total, Alexa is touted as having more than 3,000 skills and growing daily. In the workplace, artificial intelligence is evolving into an intelligent assistant to help us work smarter. Artificial intelligence is not the future of the workplace, it is the present and happening today.

On one hand, there's recent PwC findings suggesting A.I. could drive $15.7 trillion in productivity gains by 2030. On the other, a recent piece from The New York Times makes a compelling case that, despite all the hype, A.I.'s dirty little secret is that "it still has a long, long way to go." There's no question A.I. is a developing technology. As The New York Times piece points out, we can find plenty of examples of robots falling over while opening doors, driverless cars needing human intervention, and machines that still cannot read reliably at the level of a sixth grader. And while there are many "microdiscoveries" being made along the way, progress toward real human cognition remains elusive.

The Deep Learning Specialization consists of five different courses. The courses are free to take, but you need to sign up for a subscription of $49/month if you want access to the graded assignments or earn certificates. There is a seven day free trial. The individual courses are free, but you need to visit the course pages separately (you can't sign up to them from the Specialization page). Though the courses officially start on 15 August, the course materials for the first three courses are already available.

You've probably encountered the term "machine learning" more than a few times lately. Often used interchangeably with artificial intelligence, machine learning is in fact a subset of AI, both of which can trace their roots to MIT in the late 1950s. Machine learning is something you probably encounter every day, whether you know it or not. The Siri and Alexa voice assistants, Facebook's and Microsoft's facial recognition, Amazon and Netflix recommendations, the technology that keeps self-driving cars from crashing into things – all are a result of advances in machine learning. While still nowhere near as complex as a human brain, systems based on machine learning have achieved some impressive feats, like defeating human challengers at chess, Jeopardy, Go, and Texas Hold'em.

As artificial intelligence alters work done in all manner of industries, companies and governments can help workers transition by supporting incomes and facilitating skills training. The pressure is on for companies and governments to address the ways that artificial intelligence (AI) is altering the future of work. In this video, recorded at the Aspen Ideas Festival in June, experts--Markle Foundation CEO and president Zoë Baird; Joy Buolamwini, founder of the Algorithmic Justice League at MIT Media Lab; James Fallows, national correspondent of the Atlantic; and Coursera cofounder Andrew Ng--discuss how to make the transition into this new age easier for everyone. Andrew Ng: AI is the new electricity. About 100 years ago, we started rolling out electricity in the United States, and it changed every single major industry, everything ranging from healthcare and culture to transportation, communications, and manufacturing are now all electricity powered.