MW 10:10am–11:25am
Every section meets at this time.
1 of 2 sections have room
Prerequisites Prerequisites: Students should be familiar with Python programming. A basic understanding of probability and statistics at the level of IEOR E4150 (or equivalent) is required.
Description
Introduces agentic AI systems for decision-making in operations research and financial engineering. Covers large language models, retrieval-augmented generation, conversational agents, semantic workflows, and streaming architectures. Emphasizes hands-on design and deployment of end-to-end agentic pipelines, integrating forecasting, optimization, and reasoning in operational problems and financial engineering applications. Applications include supply chain risk, energy systems, inventory management, and portfolio management.
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Sections2
- MW 10:10am–11:25am · SEELEY W. MUDD BUILDING MUD 524Full
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- 98 of 99 seats left
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
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Workload and grading
- Grading
- Not published
- Format
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- Credits
- 3 credits
Reported workload
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