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

When you complete the course successfully, you will be able to:

  • Load and prepare data for downstream analysis, including text-based data
  • Describe features of the input dataset via summary statistics and informative data visualizations
  • Utilize supervised (ex: linear, logistic, and multinomial regression) and unsupervised (ex: clustering) machine learning approaches
  • Compare & contrast different machine learning models
  • Critique model fit and suggest methods for refining model accuracy
  • Effectively communicate the results of an in-depth data science analysis


This course applies toward the Bioinformatics Endeavor digital badge.

What FAES Learners are Saying

“I learned basic Python skills that will serve as a foundation for future use.” - FAES Learner

Textbook Information

There is no textbook for purchase required for this course.


Foundational understanding of statistics, probability, algebra, and calculus. 
Previous programming experience suggested.

Additional Information

This course is for learners with introductory knowledge to programming who want to learn more about data science and how to apply data science to their research, especially focused on biological datasets. 

Follow the link to review FAES Tuition Refund Policy

Funding Justification Guide

Some labs and institutes may have specific funds set aside for trainees to continue their education and professional development. FAES has created a guide intended to help trainees request funds that may be available and, if they are available, request use of the training funds for continued professional development. More details


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Section Title
Introduction to Data Science
Online Asynchronous
Jun 12, 2024 to Jul 30, 2024
Total Cost (Includes $75 non-refundable technology fee per course when applicable)
Eligible Discounts Can Be Applied at Checkout (2 Credits) $775.00
Potential Discount(s)
Available for Academic Credit
2 Credit(s)
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