Dear all,
We are thrilled to announce our upcoming online course, "Introduction to Deep Learning for Biologists," scheduled from 30th September to 4th October: https://www.physalia-courses.org/courses-workshops/course67/
Course Overview:
Our course provides a comprehensive introduction to deep learning predictive algorithms for regression and classification. We will explore the theoretical frameworks and key components behind developing deep learning models tailored for biological data. The focus will be on applying Convolutional Neural Network (CNN) architectures to real-world data for classification, regression, and image segmentation tasks. Additionally, we will delve into statistical learning principles, including performance measurement, cross-validation, overfitting risks, and model generalizability.
Course Format:
Structured over five days, the course comprises modules that include lectures, class discussions, and practical hands-on sessions. These sessions will feature collaborative exercises where participants will interact with instructors and peers to apply their newly acquired skills. We will also interpret and discuss the results of these exercises in real-time.
Learning Outcomes:
By the end of the course, participants will have gained:
- A solid theoretical foundation in deep learning, including key building blocks and state-of-the-art architectures.
- An understanding of classification, regression, segmentation, and how to frame real-world problems within these contexts.
- Knowledge of the steps involved in building deep learning models for biological prediction problems, including evaluating prediction accuracy and comparing different models.
- Skills to utilize real-world data for statistical learning, including data preparation and augmentation.
