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Lecturer/Instructor
Project Overview
Teaching computer science and economics topics:
Key Features
- Basic data structures in computer science: linear and non-linear
- Algorithm design/analysis for public policy: optimization and matching
- Scrum web app development through Git/GitHub using Flask
- AI \& ethics, HuggingFace \& agentic workflows, data mining for financial analytics, business analytics & decision making
- Principles of Bayesian modeling; Reasoning, inference, Bayesian networks/linear models/hierarchical models, Markov chain Monte Carlo & PyMC
- Fundamentals of complex adaptive systems: Non-linearity, feedback loops, adaptation, self-organization, and emergence
- Agent-based modeling of complex systems and their Bayesian calibration