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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: Anaconda installation of Python 3 in Jupyter Notebook
Duration: 180 min

Room description:

During the Fall 2021 semester, 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