shutterstock image 1145464364NSF 2D Materials Data Framework Training Workshop

November 11-15, 2018
Baltimore, MD

CLICK HERE TO REGISTER

Target Audience: This Materials Data Training Workshop is sponsored by the NSF and designed for graduate students and post-docs from research teams recently awarded NSF-2D Materials Data Framework Data Supplements

Introduction: This four-day workshop is organized by the Platform for the Accelerated Realization, Analysis, and Discovery of Interface Materials (PARADIM), an NSF Materials Innovation Platform (MIP), in partnership with the NIST Office of Data and Informatics.  

The workshop mission is to provide hands-on training to develop data-intensive knowledge and skills for DMR-2D research groups.  

Dates: November 11-15, 2018.  Arrive Sunday afternoon, first session starts at 7:00 pm.  Departure at 4:30 pm, Thursday.

Cost: Free except for registrant travel, housing ($109 plus tax for single occupancy; $129 plus tax for double occupancy) and dinner costs.  Conference facilities, training, breakfast, and lunches provided by PARADIM through NSF sponsorship.

Location: Johns Hopkins University’s Mt. Washington Conference Center, Baltimore, MD.  (https://www.acc-mtwashingtonconferencecenter.com/map--directions.html)

Details: We are in the midst of a data revolution. The confluence of information rich measurement techniques and computing capabilities to store and analyze information are rapidly changing the face of how data is collected, distributed, analyzed, and interpreted. The Materials Genome Initiative and the NSF Materials Innovation Platforms are designed to tap into this revolution as applied to materials.   
Specific curricular goals are for participants to be able to:

  • Set up and navigate within a Python environment, with emphasis on PARADIM MIP applications
  • Use Jupyter notebooks for data analysis and presentation 
  • Understand Python coding for control flow, data frames, plotting methods and basic statistics
  • Access public materials datasets and MIP data through APIs
  • Use the notebook interface for data mining and manipulation
  • Use version control for their code and analysis (via GitHub)

Specific topics include:

  1. Bash shell
  2. The basics of Python 
  3. Python packages and scripting for data analysis
  4. Introduction to databases and SQL scripting
  5. Git version control and the use of GitHub
  6. Introduction to Materials Domain Python packages
  7. Use of APIs for access to Materials datasets 
  8. Basics of Data mining, wrangling, and visualization.

Daytime classroom sessions will emphasize problem solving in small groups.  Evenings will be scheduled by the students to include free time, lightning talks, and discussion of recent advances in applications of data science and machine learning in the Materials Sciences and Engineering. A tour of the new PARADIM MIP and related facilities at JHU will also be provided.

Attendees are required to bring a laptop computer with the Chrome browser and access to the eduroam network.


For more information or questions, please email: pdc@jhu.edu.

Sponsored By:

 

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