We are delighted to announce our upcoming training course: "Introduction to Deep Learning for Biologists." This comprehensive programme will equip participants with the essential knowledge and skills to leverage deep learning algorithms for regression and classification tasks in biological research. The course will be held online from 2nd to 6th October 2023.
Course website: https://www.physalia-courses.org/courses-workshops/course67/
In this course, we will provide a solid theoretical foundation and practical guidance for developing deep learning models specifically tailored to biological data. With a particular emphasis on Convolutional Neural Network (CNN) architectures, we will address real-world challenges in data classification, regression, and image segmentation. Additionally, we will cover statistical learning concepts, including performance evaluation, cross-validation, overfitting prevention, and model generalisation.
The course will be delivered through a combination of interactive lectures, class discussions, and hands-on practical exercises. Participants will have the opportunity to collaborate with both instructors and fellow attendees, applying their newly acquired skills to solve real-world problems. The course will primarily utilise Python, Jupyter Notebooks, and the Linux command line.
Target Audience and Prerequisites:
This course is designed for advanced students, researchers, and professionals with an interest in deep learning and its applications in biology. Whether you are a beginner or an experienced user, this course caters to diverse skill levels. A background in biology and familiarity with research problems involving prediction, inference, and pattern discovery is recommended. Basic knowledge of Python programming and the Linux environment will be advantageous but not mandatory.
Learning Outcomes: By the end of this course, participants will:
- Gain a solid understanding of the theoretical foundations and commonly used architectures in deep learning.
- Differentiate between classification, regression, and segmentation tasks and effectively frame real-world biological problems.
- Acquire the necessary skills to build and evaluate deep learning models for prediction problems in biology.
- Learn how to work with real-world data, including data preparation and augmentation techniques.
Registration: Limited seats are available for this exclusive course. To secure your spot, please visit https://www.physalia-courses.org/courses-workshops/course67/. Early registration is highly recommended. Full list of our courses and Workshops: https://www.physalia-courses.org/courses-workshops