Summer Data Science Bootcamp

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Data science is revolutionizing how scientists and engineers go about their work, but most students have not had much exposure to it. This one-week bootcamp provides an opportunity to get introduced to data management and visualization, data modeling, deep learning, and scientific programming in Python. The bootcamp will consist of morning lectures, followed by hands-on sessions in the afternoon to try out and practice concepts and software tools.

The bootcamp is aimed at undergraduate and graduate students in science and engineering who have an introductory-level familiarity with any computer programming language, or MATLAB, or RStudio, etc. The bootcamp is free of charge, but enrollment is capped so students must apply by May 15, 2019. Students from Agnes Scott, Morehouse, Spelman, and Georgia Tech are particularly encouraged to apply.

Topics: Computer programming in Python for data science, clustering, numerical linear algebra, classification, regression, deep learning, and domain applications

Tools: Python, Jupyter notebooks, GitHub, NumPy, Pandas, Matplotlib, scikit-learn, and TensorFlow

Skills: Python programming, version control, social coding, data handling and visualization, data analysis, data modeling and prediction, and scientific and engineering applications

Instructors: Ryan Wade (Blue Horseshoe Solutions), Vetria Byrd (Purdue University), Edmond Chow (Georgia Tech), Xiaoming Huo (Georgia Tech), Eva Dyer (Georgia Tech), Chris DePree (Agnes Scott), and David Sherrill (Georgia Tech)

Location: Georgia Tech Campus • Visitor parking available in the W23 Parking Lot, located at 911 State St. NW.

  • Monday: Engineered Biosystems Building (EBB), Children's Healthcare Seminar Room (first floor by food kiosk), 950 Atlantic Dr., Atlanta GA 30332
  • Tuesday–Friday: Molecular Science and Engineering Building (MoSE), Room G011 (ground floor behind elevators), 901 Atlantic Dr., Atlanta, GA 30332

This bootcamp is sponsored by a National Science Foundation TRIPODS+X: EDU grant to the Data-Driven Alliance (Agnes Scott, Georgia Tech, Morehouse, and Spelman) and the Institute for Data Engineering and Science (IDEaS) at Georgia Tech.



  • Workflow Status: Published
  • Created By: A. Maureen Rouhi
  • Created: 05/31/2019
  • Modified By: A. Maureen Rouhi
  • Modified: 07/09/2019



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