Certificate in Drug Discovery: AI and Machine Learning
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⢠Introduction to Drug Discovery: Overview of the drug discovery process, its challenges and opportunities.
⢠Fundamentals of AI and Machine Learning: Basics of artificial intelligence and machine learning, including supervised and unsupervised learning, neural networks, and deep learning.
⢠Data Mining and Analysis in Drug Discovery: Techniques for data mining and analysis in drug discovery, including feature selection, dimensionality reduction, and clustering.
⢠AI and Machine Learning Applications in Drug Discovery: Exploration of AI and machine learning applications in drug discovery, including target identification, lead optimization, and clinical trial design.
⢠Natural Language Processing (NLP) in Drug Discovery: Utilization of NLP techniques in drug discovery, including text mining, named entity recognition, and sentiment analysis.
⢠Computer-Aided Drug Design (CADD) with AI and Machine Learning: Overview of CADD techniques, including molecular docking, molecular dynamics simulations, and pharmacophore modeling, and their integration with AI and machine learning.
⢠AI Ethics and Regulations in Drug Discovery: Ethical considerations and regulations in drug discovery, including bias, privacy, and data security.
⢠Emerging Trends and Future Directions in AI and Machine Learning for Drug Discovery: Overview of the latest trends and future directions in AI and machine learning for drug discovery.
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