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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

Credentials

This course applies toward the Bioinformatics Curiosity 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
Oct 26, 2022 to Dec 13, 2022
Fee Includes All Costs
Eligible Discounts Can Be Applied at Checkout credit (2 Credits) $775.00
Potential Discount(s)
Available for Academic Credit
2 Credit(s)
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