An elective course in the Python for Data Science, Web and Core Programming Specialized Studies Program.
Course closed to new registrations:
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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.
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.
Textbooks for your course may be purchased from any vendor or bookseller of your choice.
No textbooks are required for this course.
|Event||Date||Day||Start Time||End Time||Location||Room
|START||07/26/2021||Monday||---||---||Online (Access Begins)||---
|END||09/12/2021||Sunday||---||---||Online (Access Ends)||---