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Course Description

Bundle Registration! Save a bundle and receive 30% off the individual course rate when you register for both BIOF 309 and BIOF 475!

Analyzing data to generate meaningful insights and make informed predictions is fundamental to modern scientific research. This course aims to equip students with essential tools and workflows for data analysis, with a specific emphasis on biological and health-related datasets. Throughout the course, students will gain proficiency in Python-based tools, including 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

Microcredential(s)

This course applies toward the Bioinformatics Endeavor digital badge.

What FAES Learners are Saying

"I was a fan of the lecture to lab format, which made the cross from theoretical and practical material seamless. I also appreciated the weekly discussions, which promoted thinking in a practical sense about how the material we learned can be applied in real life." - FAES Learner
 

Textbook Information

There is no textbook for purchase required for this course.

Prerequisites

Foundational understanding of statistics, probability, algebra, and calculus. 
BIOF 309 or 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. 

Refund 
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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To Register Click on "Add to Cart"
Section Title
Introduction to Data Science for Biomedical Sciences
Type
Online Asynchronous
Dates
Mar 26, 2025 to May 13, 2025
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)
Instructor(s)
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