Recently HealthTech Women, a national non-profit, sat down with our Data Science instructor, Lesley Cordero to get an inside look at Artificial Intelligence, or, "AI" and how it is impacting society, particularly in healthcare and medicine.    Lesley provides her perspective in this interview in addition to a more general understanding of AI and related concepts such as machine learning, natural language processing and big data.

As long as there has been Science Fiction, the idea that machines are smarter than humans has always captivated our collective imagination. But while Artificial Intelligence (AI) has not reached that level yet, we have made considerable advances towards developing machine intelligence, as evidenced by Google, Tesla, and Uber experimenting with self-driven cars. The reason why AI has successfully burst out of universities and research labs into product is largely due to the scalability and usefulness of Deep Learning, the Machine Learning technique making this technological progress possible.

Dimensionality reduction is an important technique to overcome the curse of dimensionality in data science and machine learning. As the number of predictors (or dimensions or features) in the dataset increase, it becomes computationally more expensive (ie. increased storage space, longer computation time) and exponentially more difficult to produce accurate predictions in classification or regression models. Moreover, it is hard to wrap our head around to visualize the data points in more than 3 dimensions.

Data science is an interdisciplinary field where scientific techniques from statistics, mathematics, and computer science are used to analyze data and solve problems more accurately and effectively. It is no wonder, then, that languages such as R and Python, with their extensive packages and libraries that support statistical methods and machine learning algorithms are cornerstones of the data science revolution. Often times, beginners find it hard to decide which language to learn first. This guide will help you make that decision.

Read on how to prepare and ace the Data Science interview from our Data Scientist, Lesley Cordero. Lesley describes her experience taking the technical test at leading tech companies, including Facebook and Foursquare.

By Jithin J and Karthik Ravindra, Byte Academy

Due to an exponential increase in data in the 21st century, a new term "Big Data" was coined few years back.

Nathaniel - "Nat" - Greenwald, a statistics major in his twenties, decided to break into data science by enrolling in Byte Academy coding bootcamp.  Nat now has an exciting career working as a data integration engineer in the AdTech industry.  Read about Nat's personal experience learning to code in addition to his career tips and advice to those who may want to follow in his footsteps.

Writing a last will and testament is not usually an activity associated with millennials.  However, young people are thinking differently about protecting their families, and, in turn are "disrupting" the will industry like many others. And in doing so, they are dragging Gen Xers and Baby Boomers along with them.