http://localhost:1313/tags/training/ Training Hugo Blox Builder (https://hugoblox.com)en-usFri, 08 Nov 2024 09:00:00 +0000 http://localhost:1313/media/icon_hu_959c3fb7881ab083.png http://localhost:1313/tags/training/ http://localhost:1313/events/workshop-series/ Fri, 08 Nov 2024 09:00:00 +0000 http://localhost:1313/events/workshop-series/ <h2 id="workshop-overview">Workshop Overview</h2> <p>This intensive one-day workshop provides hands-on experience with machine learning techniques specifically designed for computational biology applications.</p> <h3 id="learning-objectives">Learning Objectives</h3> <p>By the end of this workshop, participants will be able to:</p> <ul> <li>Set up ML environments for biological data analysis</li> <li>Implement deep learning models for protein structure prediction</li> <li>Analyze genomic datasets using neural networks</li> <li>Evaluate model performance and biological relevance</li> </ul> <h3 id="schedule">Schedule</h3> <p><strong>9:00-10:30 AM</strong>: Introduction to ML for Biology<br> <strong>10:45-12:00 PM</strong>: Hands-on: Setting up DeepFold<br> <strong>1:00-2:30 PM</strong>: Genomic Data Analysis with Python<br> <strong>2:45-4:00 PM</strong>: Building Custom Neural Networks<br> <strong>4:15-5:00 PM</strong>: Project Presentations &amp; Wrap-up</p> <h3 id="prerequisites">Prerequisites</h3> <ul> <li>Basic Python programming experience</li> <li>Undergraduate-level biology or chemistry background</li> <li>Laptop with Python 3.8+ installed</li> <li>GitHub account for accessing materials</li> </ul> <h3 id="instructors">Instructors</h3> <p><strong>Dr. Michael Chen</strong> - Postdoctoral researcher specializing in ML for protein structure prediction<br> <strong>Sarah Johnson</strong> - PhD student with expertise in genomic data analysis</p> <h3 id="registration">Registration</h3> <p><strong>Capacity</strong>: Limited to 20 participants for optimal hands-on experience<br> <strong>Cost</strong>: Free (materials and lunch included)<br> <strong>Deadline</strong>: November 1, 2024</p> <h3 id="contact">Contact</h3> <p>Questions? Email or contact Dr. Michael Chen directly.</p>