In this special guest feature, Jerry Huang, Chief Operating Officer of iTutorGroup, discusses how the collection and analysis of Big Data will continue to dramatically change the landscape of learning and pave the way for optimized learning experiences, leading to even better student outcomes.
Online Education Gets Up Close and Personal as Big Data Improves Performance
April 3, 2017 by 1 Comment
Quantifying Data Science
March 25, 2017 by Leave a Comment
Our friends over at The Data Incubator just released a new series of data-driven ranking reports that showcase the quantitative methodologies the data science fellowship, hiring and training company uses to actively teach their fellows. The idea was to develop a more data-driven approach to what the company should be teaching in their data science corporate training and their free fellowship for masters and PhDs looking to enter data science careers in industry.
Making the Leap from Data Science Hopeful to Practitioner
March 9, 2017 by 2 Comments
It’s a familiar dilemma. You’ve done your research, read some books, taken some online classes – and at long last, you’re finally ready to get real-life work experience as a Data Scientist. In this contributed article, Dan Saber, Data Science Hiring Manager at Coursera, offers three important steps for successfully transitioning into a data science career.
Interview: Emily Glassberg Sands, Data Science Manager at Coursera
February 28, 2017 by Leave a Comment
I recently caught up with Emily Glassberg Sands, Data Science Manager at Coursera, to talk about applying machine learning, neural networks, natural language processing, and big data analytics to the retail industry. Emily leads an awesome team of data scientists and data science managers working on growth, discovery, the learning experience, and a new enterprise offering. The team’s job is to help build a better Coursera through data-driven decisions and products.
Making the Most of Big Data Requires Effective Training in Data Science
February 6, 2017 by 1 Comment
In this special guest feature, Devavrat Shah, professor in MIT’s Department of Electrical Engineering and Computer Science, discusses the type of training data scientists need in order to glean the most value from big data.
Book Review: Deep Learning by Goodfellow, Bengio, and Courville
December 8, 2016 by Leave a Comment
I don’t usually get excited about a new book for the field in which I’ve been deeply involved for quite a long time, but a timely and useful new resource just came out that provided me much anticipation. “Deep Learning” by three experts in the field – Ian Goodfellow, Yoshua Bengio, and Aaron Courville is destined to considered the AI-bible moving forward.
The Big Benefits of a Big Data Degree
November 4, 2016 by Leave a Comment
In this special guest feature, Lauren Willison, Director of Admissions at Florida Polytechnic University, takes a critical look at the value of an advanced degree in big data in terms of job prospects and expected salary.
Learn Data Science: Eight (Easy) Steps
October 23, 2016 by Leave a Comment
Our friends over at DataCamp have produced the “Become a Data Scientist in 8 Steps” infographic providing a view of the eight steps that you need to to through to learn data science. Some of these eight steps will be easier for some than for others, depending on background and personal experience, among other factors.
Benefits of Having a Data Scientist Career
September 23, 2016 by Leave a Comment
With the continued upward trajectory of interest in getting on board with a data science career, our friends over at Simplilearn Solutions put together the compelling infographic below.
Book Review: The Manga Guide to Regression Analysis
September 21, 2016 by Leave a Comment
Last year, I wrote a review of a useful book that got students up to speed with a key mathematical ingredient of machine learning – linear algebra: The Manga Guide to Linear Algebra. No Starch Press (an excellent source of technical books) just came out with a follow-up title: The Manga Guide to Regression Analysis.
