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Python for Data Analysis

A required course in the Python for Data Science, Web and Core Programming Specialized Studies Program.

Course Description

Python for Data Analysis is a course for students with some experience using Python who want to learn how to import and analyze data using the popular programming language. Students can immediately use what they have learned to ingest data, produce plots and analysis, and fit models. Note that not everything with-in the python language will be covered (such as user interfaces, web services, and object oriented programming). The main python libraries introduced will be numpy, matplotlib, pandas, and scikit-learn. Major topics include: how to import data and manipulate it efficiently using numpy, how to produce plots and data visualizations with matplotlib, how to run statistical analysis using pandas, and how to build predictive models scikit-learn. A final project will help to tie the main concepts together. Additional topics include: how to use eclipse, a very handy development environment! Prerequisites: I&C SCI X426.64 Introduction to Programming with Python; Knowledge of Python programming is required.

Prerequisites: I&C SCI X426.64 Introduction to Programming with Python; Knowledge of Python programming is required.

NOTE: This course may have live sessions via Zoom. A device with audio and visual will be needed to participate. The following student guide provides additional resources/information on how to use and access your courses Zoom sessions.

  • Details
  • $795
  • February 14, 2022 to March 20, 2022
  • Delivery Mode: Online
  • Reg#: 00226
  • ID/Units: I&C SCI X426.62  (1.50)
    ( Section 1 )
  • Quarter: WINTER 2022

Instructor


Instructor TBA

Textbook Information

Textbooks for your course may be purchased from any vendor or bookseller of your choice.

No textbook information is available for this course.

Meeting Schedule

EventDateDayStart TimeEnd TimeLocationRoom
START02/14/2022Monday------Online (Access Begins)---
END03/20/2022Sunday------Online (Access Ends)---