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Big Data & Data Analytics


Currently, demand for workers with analytical expertise is extremely high – join us to obtain a comprehensive introduction into the critical and practical elements of big data analytics, including: data structure, warehousing, statistics, analysis, patterns, trends, relevancy, model building, visualization techniques and more. Completion of this course can enable students to participate in big data projects as analysts. The course is best suited for individuals and college graduates interested in data-related careers, including positions as business or data analysts. Recommended: degree in or equivalent practical experience in business, science, engineering, software and/or data processing.

This course provides a comprehensive foundation in big data analytics and covers the important and practical elements of the field. Armed with this training, graduates of the course can participate in big data projects as associate data analysts.
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The course is intended and is best suited for the following prospective participants:

  • Individuals and college graduates interested in a big data career as data scientist who have already earned a degree in or equivalent practical experience in business, science, engineering, software and data processing
  • Business intelligence professionals and data analysts who are interested in becoming knowledgeable about Big Data Analytics
  • Business leaders who are contemplating the applicability and utility of big data analytics in their businesses
  • Managers and executives who are interested in becoming effective participants in the selection, implementation and competent use of big data analytic solutions in their businesses

Course Content



Topics include:

  • Big Data Fundamentals
  • Data Structure
  • Data Warehousing
  • Data Engineering Fundamentals
  • Data Mining using Rapid Miner, Azure & Python
  • Data Modeling
  • Descriptive Analytics
  • Predictive Analytics
  • Introduction of Artificial Intelligence (AI), with NVIDIA
  • Data Visualization using Tableau
  • Practicums using big data platforms and datasets
  • Spark/ Databricks


In order to reserve a seat in our September 21st program please pay a refundable $500. Please note: the remaining balance will be due in full by September 18, 2019.
Payment in full allows students the opportunity to request full access to all course materials, including video recordings, books, and more. When this option is utilized, the date of full payment will serve as the student’s ‘program start date.’

For withdrawal and refund conditions, please visit ece.emory.edu/policies.

Please call Enrollment Services at 404.727.6000 with any questions.