Course Goals: - Enable Specification of Software and AI Needs, Basic Implementation Skills - Understand opportunities and limitations of ML and AI in Healthcare
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Python Primer
- Numpy and Pandas, and https://medium.com/analytics-vidhya/simple-linear-regression-with-example-using-numpy-e7b984f0d15e
- Data Visualization
- FastAI, Pytorch
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Logic and Knowledge Representation
- Propositional Logic
- First Order Logic (Predicate Logic) Summary: https://www.teach.cs.toronto.edu/~csc110y/fall/notes/03-logic/01-propositional-logic.html
- Ontologies
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Hands-on: Planning and Implementing a simple System
- Create an Ontology (OWL)
- Use Python for Inference
- Build Simple Frontend
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Machine Learning
- From data to patterns to inference
- Case Study: Recommender Systems in Healthcare
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Deep Learning
- Deep Learning and Generative AI
- Case Study: Bio GPT
Artificial Intelligence - A modern Approach https://ebookcentral.proquest.com/lib/th-deggendorf/detail.action?docID=6563527