Course Overview

Course Descriptions
This three-week course at Taipei Medical University builds on the “Artificial Intelligence in Bioinformatics” course to enhance practical skills in AI applications for bioinformatics. Through real-world case studies, participants will learn to use WEKA, a Java-based tool, for collecting and analyzing bioinformatics data. Topics include AI in genome sequencing, protein function prediction, and gene expression. The course also covers deep learning concepts like CNNs, RNNs, and NLP, focusing on their bioinformatics applications. By the end, learners will be equipped with the skills to apply AI in research and data visualization, and to contribute to bioinformatics innovations.

Total Learning Hours
Total learning hours of 3 hours

Learning Objectives
1. Learners can apply machine learning and deep learning to solve bioinformatics problems.
2. Learners able to apply bioinformatics papers suitable for publication.
3. Learners can analyze and visualize bioinformatics data for reporting results.

Target Learners
This course is designed for any student, biologist, or researcher who would like to learn the basics of using AI to study bioinformatics data. It follows on from our short course ‘Artificial Intelligence in Bioinformatics’ which we recommend taking first to develop your foundation of knowledge beforehand.

Evaluation
Unit Quizzes 40% graded
Final Exam 60% graded
Learners requires no less than 70% in order to pass the course and eligible to receive the certificate