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Introduction to Data Science II
July 7 - August 28, 2020
Equipped with an introductory understanding of Python and data science topics from Data Science I, Data Science II will expose learners to more advanced models, techniques, and other important big data topics. Common machine learning models will be covered comprehensively from their mathematical formulation (e.g., least squares equations for regression) and model training (e.g., stochastic gradient descent) to their practical implementation (e.g., regularized regression in Python) and evaluation on real datasets. More advanced Python topics (e.g., objects and classes) will also be covered for learners to understand how build reusable modules implementing custom data science methods.
Registration in this course is subject to the Purdue Online Non-Credit Policies.
No sections currently available.