About the Course
Daily production of data has reached 2.5 million terabytes in 2016 and is expected to increase exponentially. In this two-day hands-on course, participants will familiarize themselves with the building blocks of big data, experiment with statistical and data management tools like R, Mongo DB, and Hadoop, and perform predictive modeling and analytics exercises that turn data into valuable and actionable knowledge.
- Understand key concepts in big data analytics
- Appreciate the value of big data analytics for the various industry domains
- Use advanced technological tools to analyze the data
- Apply statistical techniques to make inferences
- Learn how to drive organizational value by producing actionable knowledge from clearly framed problems
- Enhance their marketability in the growing and promising space of big data jobs
Who Should Attend?
The ideal participant is a mid- or upper-level industry professional and leader with a strong interest in exploiting Big Data analytics to improve the performance of their organization. Vice presidents, chief officers, and senior managers in different domains including strategy, finance, human resources, management, and marketing as well as consultants, bankers, accountants, healthcare executives, investors, and journalists would benefit the most from the program. The course will also be of interest to young graduates who wish to explore new work opportunities in the field of data science.
The participants must have basic knowledge of statistics, data structures, and programming. They will also be asked to bring their own laptops and to install the open-source software required for the workshops and exercises.
About the Speaker
Assistant Professor of Information Systems at Qatar University.
Mazen El-Masri is an assistant professor of information systems in the Department of Accounting and Information Systems of the College of Business and Economics at Qatar University. He obtained his Ph.D. in management information systems from HEC Montréal, Canada. He teaches data science (graduate), big data analytics, information security (graduate), introduction to Management Information Systems, and IT project management.
El-Masri’s work appears in IT & People, Educational Technology Research and Development, Journal of Information Systems Education, ACIS, ICIS, AMCIS, ECIS, PACIS, and ASAC. His research includes text analytics, e-learning, gamification, predictive modeling, IT project risk, big-data, social networks, and semantics.
2- Day Program Agenda: April 15 & 17
|April 15||April 17|
|7:45 a.m. – 8:15 a.m.||Breakfast and registration||Breakfast and discussion of big data analytics in the 2016 U.S. presidential election|
|8:15 a.m. – 9:45 a.m.||Current understanding of Big Data and analytics processes in organizations||Statistical modeling|
|10:15 a.m. – 11:45 a.m.||Data structures – data management systems||Big data text analytics|
|12:00 a.m. – 1:15 p.m.||Networking lunch and food for thought: Speaker I||Networking lunch and food for thought: Speaker II|
|1:15 p.m. – 2:30 p.m.||Data treatment||Exercises in predictive modeling|
|2:45 p.m. – 4:00 p.m.||Exercises in data management and manipulation||Career and ethical issues in data science|
|4:00 p.m. – 4:15 p.m.||Debriefing||Debriefing and award ceremony|