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Data Preparation, Modeling and Visualization with Python

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

Course closed to new registrations: Call ( 949 ) 824-5414 for more information or sign up below to be notified when this course becomes available.×

Course Description

Learn how to create business value by effectively importing, preparing, modeling and visualizing data using the Python programming language. Students will learn how to implement various models like linear regression, logistic regression, and decision trees; both supervised and unsupervised modeling techniques will be covered. Pandas and scikit-learn will be the primary Python packages covered in this course. Both of these packages provide power tools for those in machine learning, data science, data mining, and web data professions.

Prerequisites: I&C SCI X426.64 Introduction to Programming for Python or I&C SCI X426.62 Python for Data Analysis.

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.

  • Be notified when this class becomes available!

  • Details
  • $820
  • May 02, 2022 to June 19, 2022
  • Delivery Mode: Online
  • Reg#: 00239
  • ID/Units: I&C SCI X426.54  (2.00)
    ( Section 1 )
  • Quarter: SPRING 2022

Instructor


William J. Henry, M.S., is a scientific programmer at the Navy Research Laboratory in Monterey where he regularly develops data based applications in Python. Previously, at EarthRisk Technologies, he led the development of a neural network ensemble temperature forecast model.

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
START05/02/2022Monday------Online (Access Begins)---
END06/19/2022Sunday------Online (Access Ends)---