The 24 hours training aims to introduce the concepts, terminologies and IBM technologies available today to process, operate, and maintain Big Data repositories to further help executives to make decisions and to understand the sentiments of data at certain domain. The training aims to presents the successful uses cases of Big Data in today’s business. The training is intended to provide a broad introduction into the Big Data technologies and their related ecosystem.
Senior executive managers, senior undergraduate computer and business students, post graduate students, IT staff, and business users who are interested in Data Science.
Basic knowledge of computer and Information Technology concepts. Superficial knowledge of Linux and programming concepts.
Advantageous: R and Python programming skills. Jupyter for data scientist.
Textbook and Articles:
- Lecture Notes will be distributed during the training.
- White, T. (2015). Hadoop: The definitive guide (4th, revised & updated ed.). Sebastopol, CA: O'Reilly Media. ISBN 978-1-491-90163-2. 756pp.
- Zikopoulos, P., deRoos, D., Bienko, C., Buglio, R., & Andrews, M. (2015). Big data beyond the hype: A guide to conversations for today’s data center. New York: McGraw Hill Education.
- Google’s Paper on Big Table: http://research.google.com/archive/bigtable.html
Desktop / Notebook Requirements:
- Windows 7+ Pro, or preferably Windows 10 Pro, 64-bit, 8 GB RAM (16+ GB strongly preferred), 100 GB available disk (or a 500GB+ external USB drive).
- Apple computers with a recent version of Mac OS X can be used, but all directions given throughout the course will be for Microsoft Windows 10 environments exclusively. Again, minimal memore if 8 GB RAM, with 16+ GB strongly preferred.
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Dr. Abedallah is a Software Engineering Ph.D holder. He is an assistant professor at the AUE. He is an active researcher in the software cost estimation field, empirical software engineering studies, and functional size measurement.