Drug discovery is a notoriously risky and expensive process. AI-driven drug discovery has emerged rapidly in recent years, to become a major avenue for biotechnology and pharmaceutical companies to gain faster and cheaper access to drug therapeutics. This course is intended to introduce learners to the application of AI/ML and computational data analysis in drug discovery.
- Graduate Certificate in Artificial Intelligence and AI Plus
- FlexiMasters in Artificial Intelligence and AI Plus
At the end of the course, learners are able to:
- Understand the basics of drug discovery and how AI/ML can be applied to accelerate various phases of drug discovery, specifically in drug screening
- Understand the basics of drug-protein interactions and how AI/ML can be applied to predict drug targets
- Identify a problem in the drug discovery process, formulate a solution, and evaluate appropriate algorithms to solve the problem.
- Predict protein interactions, protein complexes, and disease genes.
In this course, we introduce the phases of drug discovery and different machine learning methods that can be embedded into the drug discovery process to facilitate drug target identification and drug design. The course is intended to be a foundation course for Computer/software learners who are interested to pursue a career in the biomedical/pharmaceutical domain. For computer science learners, the course is intended to be an introductory course to biological problems in the biomedical/drug discovery domains, and that can be addressed using AI/ML applications. Through studies of different AI/ML methods, the learners will also enhance their ML skills. For biology/biomedical learners, the course is intended to be a foundation course in AI/ML. It mainly covers:
- Introduction to AI-driven Drug Discovery (Understanding the drug discovery process; introduction to drug screening and drug design; Introduction to prediction/machine learning methods used in various phases of the drug discovery process)
- Image-based machine learning for quantifying drug response in screening
No pre-requisites are needed to enrol in the individual courses.
Participants need to take note that those without qualifications or prior working experience in relevant engineering or the related fields, may find the course contents challenging.
Standard Course Fee: S$1,944
SSG Funding Support
Course fee payable after SSG funding, if eligible under various schemes
Fee BEFORE funding & GST
Fee AFTER funding & 8% GST
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding)
Enhanced Training Support for SMEs (ETSS)
SCs aged ≥ 40 years old
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
Select one of the following options:
|COURSE TITLE||ACADEMIC UNIT|
|AI for Advance Manufacturing and Engineering|
|CET870 AI for Advanced Manufacturing and Engineering (Basic)||1|
|CET871 AI for Advanced Manufacturing and Engineering (Intermediate)||1|
|CET872 AI for Advanced Manufacturing and Engineering (Advanced)||1|
|AI for Bioimage, Signal Analysis & Healthcare|
|CET873 AI for Bioimage, Signal Analysis & Healthcare (Basic)||1|
|CET874 AI for Bioimage, Signal Analysis & Healthcare (Intermediate)||1|
|CET875 AI for Bioimage, Signal Analysis & Healthcare (Advanced)||1|
|AI for Business Analytics|
|CET876 AI for Business Analytics (Basic)||1|
|CET877 AI for Business Analytics (Intermediate)||1|
|CET878 AI for Business Analytics (Intermediate)||1|
|AI for Drug discovery & Protein Interactions|
|CET880 AI for Drug discovery & Protein Interactions (Intermediate)||1|
|CET881 AI for Drug discovery & Protein Interactions (Advanced)||1|
|AI for Computational Geonomics|
|CET882 AI for Computational Geonomics (Basic)||1|
|CET883 AI for Computational Geonomics (Intermediate)||1|
|CET884 AI for Computational Geonomics (Advanced)||1|
|AI for Accelerated Materials Development|
|CET885 AI for Accelerated Materials Development (Basic)||1|
|CET886 AI for Accelerated Materials Development (Intermediate)||1|
|CET887 AI for Accelerated Materials Development (Advanced)||1|
|AI for Smart City and Urban Systems|
|CET888 AI for Smart City and Urban Systems (Basic)||1|
|CET889 AI for Smart City and Urban Systems (Intermediate)||1|
|CET890 AI for Smart City and Urban Systems (Advanced)||1|
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Artificial Intelligence and AI Plus (total 9AUs) and FlexiMasters in Artificial Intelligence and AI Plus (total 15AUs).