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Python for Informatics

Informatics is the study of structure, algorithms, behavior, and interactions of information systems. Its applications are powerful and broad, and include such fields as life sciences, data mining, business analytics, and social computing.

This hands-on course introduces the Python programming language, and is targeted toward students without prior programming experience who are interested in how informatics can be employed to provide solutions to complex, data intensive problems in a variety of scientific and business domains. After learning the core syntax and elements of the Python language, students will gain experience in the fundamentals of network programming, web services, databases and Structured Query Language (SQL), and data visualization.

Topics include:

  • Variables, expressions, and statements
  • Conditional execution and functions
  • Iteration and strings
  • Files and lists
  • Dictionaries and tuples
  • Regular expressions and network programming
  • Web services, database connectivity, and Structured Query Language (SQL)
  • Data visualization
  • Automation through scripting

Practical experience:

  • Write programs using the core Python language elements
  • Create IPython Notebooks to document coding sessions
  • Use Python to explore network programming, web services, databases, PySQL, and data visualization

Software: Students will use Python 2.7 and 3.X in this course. There is no additional cost to access this software.

Course typically offered: Online in Winter and Summer; In-class in Fall and Spring

Prerequisites: None.

Next Steps: Upon completion of this course, consider taking other courses in data science to continue learning.

More Information: For more information about this course, please contact unex-techdata@ucsd.edu.

Note: For in-class sections, students will need to bring a laptop to class.

Course Number: CSE-41225
Credit: 3.00 unit(s)
Related Certificate Programs: Applied BioinformaticsBusiness Intelligence AnalysisData Mining for Advanced Analytics

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