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Course Description

Learning from data in order to make useful predictions or obtain insights is a cornerstone of modern science. The goal of this course is to introduce students to the basic tools and workflows for doing this, with a focus on biological- and health-related data. In this course, students will learn how to use Python-based tools, particularly Numpy, SciKit-learn, Pandas, and Matplotlib.

Learner Outcomes

  • Load and clean data
  • Choose what type of model (e.g. supervised or unsupervised) to use based on the questions being asked of the data
  • Build and validate the chosen model
  • Visualize and explain what that model learned from the data

Microcredential(s)

This course applies toward the Bioinformatics Endeavor digital badge.

Prerequisites

There are no prerequisites for this course.

REFUND
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Section Title
Introduction to Data Science
Type
Online Asynchronous
Dates
Mar 29, 2023 to May 16, 2023
Total Cost (Includes $75 non-refundable technology fee per course)
Eligible Discounts Can Be Applied at Checkout (2 Credits) $775.00
Potential Discount(s)
Available for Academic Credit
2 Credit(s)
Instructor(s)
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