Stanford Dean of Engineering leads Big Data short course at Ashesi

July 10, 2018
May 25 – 29, 2018: Over the course of the week at Ashesi, faculty, staff, and students alike participated in a crash course on Big Data led by Jennifer Widom, Dean of Engineering at Stanford University. Backed by grants from Very Large Data Bases Foundation, Association of Computing Machinery, Google and Standford, Widom has been traveling across different countries over the past year teaching Big Data at various institutions.

This year, Ashesi University welcomed her here in Ghana, where she shared tools and techniques on how to harness big data.

“There is so much data that we gather about everything, and people are anxious to know how to harness their data,” she said. “Everybody needs that expertise, and there are a lot of people in the social sciences, who don’t have the tools they need to work on the data that is available to them. So I try to teach it at a level that can be suitable for everybody.”

For Mercy Guriyire ‘17, Faculty Intern in the Business Administration Department, the class was especially valuable for people who are not in the tech fields or privy to such skills.

“When I signed up for the class, I was expecting a less programming intensive class, but the course was very hands-on,” she said. “Despite some undeniably difficult context, the class was easy to understand and follow even for someone who had little knowledge in programming. Data is driving everything, from health to law to agriculture. So, understanding how to make sense of data is important and needed in everyday work. I’ll be using these skills now in every way, and I believe if African countries can make use of the data we have available, it will help transform our continent.”

Widom hopes that her Big Data session at Ashesi will have a snowball effect, where many other institutions in Ghana and beyond will learn about the field and how to utilize it effectively.

“I hope people will benefit from knowing tools and techniques they can use,” she said. “I also hope that some of the lecturers and Faculty Interns who are taking this course will use the material themselves or the teaching style which is designed to be highly interactive, in teaching other people For me that’s leverage; that more people can learn it and share with others.”

Widom’s aspirations are not far-fetched. Selasi Gborglah ‘18, a recent graduate, found the class as a great primer for courses she hopes to take in graduate school.

“I was quite amazed about how broad big data is,” she said. “Our society needs to take more advantage of it in as many areas as possible. Following this experience, I look forward to exploring Data Science and Analytics as part of my Masters, and eventually in a Consulting Career.

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