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Data Science 101: Excel Tutorial on Analyzing Large Data Sets

Data Science

Our friends over at Udemy partnered with data scientist David Taylor (specialist in data spelunking and visualization) to create a fun (and free) Excel tutorial on analyzing large data sets.

Data Science 101: Deep Learning – Intelligence from Big Data

Data Science

From the Stanford Graduate School of Business, we have a compelling panel discussion – Deep Learning: Intelligence from Big Data.” A machine learning approach inspired by the human brain, Deep Learning is taking many industries by storm.

Data Science 101: Automating Analytics

Data Science

For the latest installment of our Data Science 101 series, we have Bjorn Johansson, Executive Director Operations at Ericsson, presenting several initiatives where Ericsson is applying new methods to accelerate business transformation work.

Data Science 101: Fireside Chat with Andrew Ng


The topic of Deep Learning is receiving considerable play in the data science community as of late. The fireside chat video below featuring Dr. Andrew Ng offers a unique perspective on this dynamic field.

Data Science 101: What’s Coming for Spark in 2015


Apache Spark took the data science world by storm in 2014 as a technology foundation for big data applications. In the talk below from the Bay Area Spark User Meetup, Patrick Wendell from Databricks speaks about new developments in Spark and identifies areas of focus in the coming year.

Data Science 101: Machine Learning – The Basics

The next installment of insideBIGDATA’s Data Science 101 series comes from our friends over at LinkedIn.

Data Science 101: Random Forests


The Random forests machine learning algorithm is a popular ensemble method used by many data scientists to achieve good predictive performance in the classification regime. Fully understanding the nuances of this statistical learning technique is paramount to getting the most out of this algorithm – unfortunately, this means math. The presentation below is from machine learning course CPSC 540 at The University of British Columbia,

Data Science 101: Using Statistics to Predict AB Testing


The talk below presents simple methods that can accurately predict future performance from AB test results, and that allow you to determine the smallest acceptable sample size. Using four years of AB testing data, you’ll see how these methods really work.

Data Science 101: Lessons Learned from Kaggle Competitions


In the video presentation below, “Machine learning best practices we’ve learned from hundreds of competitions,” Ben Hamner, Chief Scientist at Kaggle, discusses some very intriguing insights into how find success in data science projects.

Data Science 101: Expressing Yourself in R

Brought to you by our friends over at the Stanford Center for Professional Development is this compelling data science education resource: “Expressing yourself in R” – by Hadley Wickham, Rice University.