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Data Services Class Descriptions

Information, materials, and schedules for all currently offered Data Services classes.
This is a hands-on workshop focused on getting started with writing Python code and covers basic concepts and ideas working up to a realistic web-scraping example.
Software:

Computer workstations with Anaconda Python/Jupyter Notebook are available for in-person tutorials in Bobst 617. For remote tutorials, while some patrons decide to approach tutorials as a demonstration of the software, other patrons approach tutorials with a more “hands-on” approach and wish to interact with the software during the tutorial. If the latter is the case, we recommend referencing our supported software page for additional information on accessing the software prior to the tutorial.
Duration: 180 min

Room description:

Some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering
Prerequisites: Basic computer literacy, understanding files and folders
No prior programming experience is necessary.
Skills Taught / Learning Outcomes:
  • Python interface
  • Data types (integers, floating point numbers, strings, booleans, dictionaries, lists)
  • Indexing data structures
  • Conditional statements and logical operations
  • Loops
  • Functions
  • Putting it all together in a basic web scraping example
Class Materials:
Related Classes:

Data Visualization with Tableau

Data Cleaning Using OpenRefine

Introduction to Jupyter Notebooks

Introduction to Research Data Management

Introduction to R
Additional Training Materials: guides.nyu.edu/python
Feedback: bit.ly/feedbackds

 

Upcoming sessions for this tutorial

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