Here’s a good article answering a very common question asked by folks who want to further shift their career focus into analytics, cloud computing, data science, and machine learning.

Breaking into the field of data science has to be navigated before launching into a career. Earning a job in data science isn’t easy, especially since there are extra job seekers in this analytics jobs.

Given the rise of data science and machine learning as an in-demand career, many people are wondering how to get started as a Data Scientist. Forbes explores how to get started in this article.

Many people are looking to break into data science, from undergraduates to career changers, have asked me how I’ve attained my current data science position at Pacific Life. I’ve referred them to many different resources, including discussions I’ve had on the Dataquest.io blog and the Scatter Podcast. In the interest of providing job seekers with a comprehensive view of what I’ve learned that works, I’ve put together the five most valuable lessons learned. I’ve written this article to make your data science job hunt easier and as efficient as possible.

Data Scientist was the hottest job title of the last few years. Recently, a new challenger has risen to top of the heap: Machine Learning Engineer. Part and parcel of being an ML Engineer is a solid understanding of deep learning.

Edureka has compiled a list of top deep learning interview questions you must know the answers to in order to ace any interview.

From the article:

Artificial Intelligence is going to create 2.3 million Jobs by 2020 and to crack those job interview I have come up with a set of Deep Learning Interview Questions. I have divided this article into two sections:

The battle for top talent in the AI space is heating up with Apple looking to boost their AI stable. This reminds me of the 90’s when major tech firms would poach talent from each other with impunity. It’s interesting to see how “hot” AI skills have become.

Artificial Intelligence Apple has poached another top engineer from Google as it continues to grow its artificial intelligence and machine learning divisions, with Google’s Dr. Ian Goodfellow having left his role as a “Senior Staff Research Scientist” with Google to join Apple as a “Director of Machine Learning” in […]

Recently, I was on the Workforce Show new segment “Breaking the AI Code” hosted by Swathi Young. Press the play button below to listen here or visit the show page.

Frank La Vigne works at Microsoft as an AI Technology Solutions Professional where he helps companies achieve more by getting the most out of their data with analytics and AI. He also co-hosts the DataDriven podcast. He blogs regularly at FranksWorld.com and you can watch him on his YouTube channel, “Frank’s World TV” (FranksWorld.TV). Frank has extensive experience as a software engineer. You can find him on Twitter at @tableteer

Last week, I spoke to a group of high school students about careers in STEM. Aside from being happy that STEM is now encouraged, I pointed out to them that the workforce they will be entering may look different than the one they see now.  By the time they hit the workforce, digital transformation will have made short work of companies that have not become data driven. The only surviving and thriving companies will be the one who adapted quickly. 

Proving that point is this article from TechRepublic and helpful advice on how to stay ahead of the robots.

Here’s an interesting video related to the article:

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If there ever was a case for AI, this could be a compelling one: Resume writing. It’s a task many job seekers see as a necessary evil and it seems as  everyone has an opinion about how to carefully craft the perfect document.

A new website can write your résumé for you in just ten seconds — as long as you don’t mind sending employers a document of totally-made-up information and just a touch of gibberish.