COMPUTER COMMUNICATNS NETWORKS
Analytical approach to the design of (data) communication networks. Necessary tools for performance analysis and design of network protocols and algorithms. Practical engineering applications in layered Internet protocols in Data link layer, Network layer, and Transport layer. Review of relevant aspects of stochastic processes, control, and optimization.
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Instructor:
Javad Ghaderi
h-index: 17 Info - 3 points
INTERNET ECON, ENG & SOCIETY
Mathematical models, analyses of economics and networking interdependencies in the internet. Topics include microeconomics of pricing and regulations in communications industry, game theory in revenue allocations, ISP settlements, network externalities, two-sided markets. Economic principles in networking and network design, decentralized vs. centralized resource allocation, “price of anarchy,” congestion control. Case studies of topical internet issues. Societal and industry implications of internet evolution.
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Instructor:
Debasis Mitra
Wikipedia h-index: 61 Info - 3 points
TOPICS IN SIGNAL PROCESSING
TPC:REINFORCEMENT LEARNING
Advanced topics in signal processing, such as multidimensional signal processing, image feature extraction, image/video editing and indexing, advanced digital filter design, multirate signal processing, adaptive signal processing, and wave-form coding of signals. Content varies from year to year, and different topics rotate through the course numbers 6880 to 6889.
TOPICS IN COMPUTER SCIENCE
SCALING LLMS SYSTEMS OPT
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
- 3 points
TOPICS IN COMPUTER SCIENCE
DESIGN FOR GENERATIVE AI
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
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Instructor:
Lydia Chilton
CULPA: 3 h-index: 18 Info - 3 points
TOPICS IN COMPUTER SCIENCE
HIGH PERF MACH LEARNING
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
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Instructor:
Kaoutar El Maghraoui
Info - 3 points
TOPICS IN COMPUTER SCIENCE
LLM BASED GENERATIVE AI
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
- 3 points
TOPICS IN COMPUTER SCIENCE
SCALING LLMS SYSTEMS OPT
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
- 3 points
TOPICS IN COMPUTER SCIENCE
ALGOS LARGE LANG MODELS
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
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Instructor:
Alexandr Andoni
CULPA: 2 h-index: 34 Info - 3 points
TOPICS IN COMPUTER SCIENCE
DESIGN FOR GENERATIVE AI
Selected topics in computer science (advanced level). Content and prerequisites vary between sections and semesters. May be repeated for credit. Check “topics course” webpage on the department website for more information on each section.
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Instructor:
Lydia Chilton
CULPA: 3 h-index: 18 Info - 3 points