| File Name: | Machine Learning in Drug Discovery and Cheminformatics |
| Content Source: | https://www.udemy.com/course/machine-learning-in-drug-discovery-and-cheminformatics/ |
| Genre / Category: | Other Tutorials |
| File Size : | 890.4 MB |
| Publisher: | Khalid Mostafa |
| Updated and Published: | March 1, 2026 |
This course is designed for all levels, from beginners who are new to programming and machine learning, to intermediate learners who want to apply AI in real drug discovery workflows. You will learn how to combine Python, Machine Learning, AI, and Cheminformatics to build practical solutions used in modern computational drug discovery.
What You Will Learn:
- Python fundamentals for scientific computing
- Data handling and preprocessing
- Molecular representations (SMILES, molecular fingerprints)
- Building and evaluating Machine Learning models
- Understanding R², RMSE, and model performance
- Virtual screening workflows
- ADMET filtering concepts
- How to build real-world drug discovery projects
Practical, Project-Based Approach
This is not a theory-only course.
You will:
- Build real Machine Learning Project in Cheminformatics models
- Build real QSAR models
- Generate molecular fingerprints using RDKit
- Perform virtual screening on compound libraries
- Apply AI to predict biological activityBy the end of the course, you will understand how machine learning is applied in real computational drug discovery pipelines.
Who This Course Is For:
- Pharmacy students and Pharmacists
- Chemistry and life science students
- Bioinformatics and cheminformatics learners
- Data science students interested in healthcare
- Anyone who wants to apply AI in drug discovery
DOWNLOAD LINK: Machine Learning in Drug Discovery and Cheminformatics
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