A Priceless Collaboration: IBM Watson and Udacity

Armen Pischdotchian - IBM Watson - Udacity

IBM Watson has captured our collective imagination to a degree that very few technologies ever achieve. Even to refer to it as a “technology” seems limiting, considering its larger-than-life persona. From that fabled moment in 2011 when IBM Watson won Jeopardy’s first place prize—besting legendary former champions Brad Rutter and Ken Jennings—its place in our cultural history was assured. But behind all the media notoriety lies a system of staggering power and complexity, with the potential to impact our future in ways we’re only just beginning to imagine.

In light of all this, it’s difficult at first to conceive that anyone could actually teach people about IBM Watson. But that’s exactly what Armen Pischdotchian does for a living. By title, he is an “Academic Tech Mentor at IBM Watson.” Translation: Armen Pischdotchian knows a LOT about IBM Watson.

Which is why we’re so excited for our Artificial Intelligence students, because Armen Pischdotchian is now a contributing expert for Udacity’s Artificial Intelligence Nanodegree program!

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Using Practical Empathy to Improve Product Design and Collaboration

Indi Young, Udacity Interview, Practical Empathy

In her latest book, Practical Empathy: For Collaboration and Creativity in Your Work, Indi Young offers practical tips for developing deep listening skills. While conventional product design focuses on solutions, Indi recommends developing an empathic mindset to focus on people. By learning to listen deeply, you can go beneath the surface to understand the reasoning, reactions, and guiding principles that influence people’s behaviors, thinking patterns, and perspectives.

I spoke with Indi Young to learn about practical empathy, and to explore how Udacity students can use deep understanding to make better decisions, improve product design strategies, and collaborate more successfully.

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How To Prepare For A Machine Learning Interview

Machine Learning Interview

Getting ready for a job interview has been likened to everything from preparing for battle, to gearing up to ask someone out on a date, to lining up a putt on the 18th green at The Masters. Meaning, at best, it’s nerve-racking, and at worse, it’s terrifying! Preparing for a Machine Learning interview is no different. You know you’ve got something ahead with the potential to be either really great, or really terrible. But how do you ensure your result is the great one?

It’s all about mindset, and preparation.

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Taking The Mystery Out Of Technical Interviews

TechIntCourse_Blog

New Course Launch!

I’m ecstatic to announce the launch of Udacity’s newest course: “Technical Interview | Algorithms and Data Structures in Python.” But what is a technical interview, and what specific skills do you need to master, in order to perform well in one?

Let’s start by talking about “the technical interview”. When you’re interviewing for pretty much any job that requires coding, you’ll be asked a mix of behavioral, job-skills, and algorithmic questions. Behavioral questions are meant to assess personality traits, and usually revolve around your actions in past experiences and hypothetical situations. Questions related to job skills focus on your knowledge as it applies directly to the job you’re interviewing for, like your ability to use classifiers if you’re applying for a data science job or whether you really know the Activity lifecycle as an Android developer. Algorithmic questions are meant to provide your potential employer with insight into your thought processes. You’re normally given a vague problem and asked to write code in your language of choice to solve it within a time limit.

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