The DataScience@SMU Blog


Big Data Ethics: Privacy

This blog series will examine the four main considerations of big data ethics as defined by the Council for Big Data, Ethics, and Society, specifically privacy, security, equality and access. Here, guest author Jim Harris explores the element of privacy.

Kids and Computer Science [Infographic]

In this infographic, DataScience@SMU explores the state of computer science and coding education for K-12 students around the world and in the United States, the challenges to bringing computer science education to American students, and the cognitive and social benefits of a society where more kids are fluent in code.

Data Scientists Who Launched the Field

Long before data analysis, data mining and data visualization were popular, there were pioneers carving a path through the nascent field of data science – helping to create a vision for what data could do when used in new and creative ways. Here, we take a look at five of the top data scientists who launched the field and what they have contributed along the way.

DataScience@SMU’s Inaugural Immersion

It marked the first time our students had met in person, but many felt they had known each other for years. Students arrived at the Southern Methodist University campus for a weekend of networking, career advice, case study work and the chance to finally get the SMU experience firsthand.

DataScience@SMU FAQs Answered by Professor Monnie McGee

DataScience@SMU recently hosted a curriculum webinar that featured a Q&A portion with Professor Monnie McGee and prospective students. Dr. McGee provides prospective students with an overview of what to expect in the program, the types of skills they will acquire through the program, and how data science compares to traditional statistics and analytics.

You’ve Read the Book, Now Listen to the Podcast

If you’re a data science enthusiast, you’ve doubtless read many of the classic books that cover the field. Here are six of the best data-science-oriented podcasts to listen to if you’re a fan of popular data science books.