Artificial Intelligence and Computational Drug Discovery and Development
Curriculum
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CDD 201 Techniques in Drug Discovery
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CDD 202 Python and R (NumPy, Pandas, PyTorch, Matplotlib), Web Application Development (Flask, Streamlit, Shiny)
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CDD 203 AI and ML (Supervised, Unsupervised, Semi-supervised, Reinforcement Learning); Sub-fields of ML; Generative AI
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CDD 204 Drug Development Regulations and Software Platforms (WinNonlin, SimCYP)
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CDD 205 Pharmacometrics, Systems Pharmacology and Pharmacogenomics
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CDD 206 Big Data Mining and Analysis (Real-World Data and Real-World Evidence)
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CDD 207 Modeling for Clinical Pharmacology
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CDD 223 Emerging technologies: Large Language Models (LLM)
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BIOSTAT 272 Foundations in Biostatistical Principles and Methods
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Grad Studies 214 Responsible Conduct of Research and Rigor & Reproducibility