Teaching

The current course catalog for the Northwestern CS Department is available here.

Fall 2024

• COMP_SCI 212: Mathematical Foundations of CS Part 1: Discrete mathematics for computer science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 335: Intro to the Theory of Computation
• COMP_SCI 396: Online Markets
• COMP_SCI 396, 496: Foundations of Quantum Computing and Quantum Information
• COMP_SCI 496: Graduate Algorithms
• COMP_SCI 396/496: Approximation Algorithms
• COMP_SCI 497: Calibration (Foundations of Trustworthy ML)

Spring 2024

• COMP_SCI 212: Mathematical Foundations of CS Part 1: Discrete mathematics for computer science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 262: Mathematical Foundations of CS Part 2: Continuous mathematics for computer science
• COMP_SCI 396: Differential Privacy: from Foundations to Machine Learning

Winter 2024

• COMP_SCI 212: Mathematical Foundations of CS Part 1: Discrete mathematics for computer science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396, 496: Foundations of Quantum Computing and Quantum Information
• COMP_SCI 496: Advanced Topics in Modern Cryptography

Fall 2023

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 335: Intro to the Theory of Computation
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396, 496: Advanced Algorithm Design through the Lens of Competitive Programming
• COMP_SCI 496: Foundations of Reliable Machine Learning
• COMP_SCI 496: Learning in Networks

Spring 2023

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396: Differential Privacy: from Foundations to Machine Learning
• COMP_SCI 496: Theoretical Foundations of Data Science

Winter 2023

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 332: Online Markets
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396, 496: Advanced Topics in Modern Cryptography
• COMP_SCI  396/496: Approximation Algorithms
• COMP_SCI 396: Special Topics in Social Networks

Fall 2022

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 335: Introduction to the Theory of Computation
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396: Introduction to Cryptography
• COMP_SCI 396, 496: Introduction to Kolmogorov Complexity
• COMP_SCI 496  Modern Discrete Probability
• COMP_SCI 497: Data Economics
• COMP_SCI 497: Learning Augmented Algorithms

Spring 2022

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 335: Introduction to the Theory of Computation
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396: Online Markets
• COMP_SCI 396: Theory of Data and Decisions
• COMP_SCI 496: Algorithms for Big Data
• COMP_SCI 497: Topics in Combinatorial Optimization

Winter 2022

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 396, 496: Advanced Algorithm Design through the Lens of Competitive Programming
• COMP_SCI 396, 496: Foundations of Quantum Computing and Quantum Information
• COMP_SCI 396, 496: Advanced Topics in Modern Cryptography
• COMP_SCI 396, 496: Introduction to Kolmogorov Complexity
• COMP_SCI 496: Graduate Algorithms

Fall 2021

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 496: Foundations of Reliability and Robustness in ML
• COMP_SCI 496: Mechanism Design

Spring 2021

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 496: Learning, Information, and Data
• COMP_SCI 496: Theoretical Foundations of Data Science
• COMP_SCI 497: The Science of Law and Computation

Winter 2021

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI  396/496: Analysis of Boolean Functions
• COMP_SCI  396/496: Approximation Algorithms

Fall 2020

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 335: Introduction to the Theory of Computation
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 496: Graduate Algorithms

Spring 2020

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 496: Graduate Algorithm
• COMP_SCI 496: Algorithmic Aspects of Network Inference
• COMP_SCI 396, 496: Advanced Topics in Approximation Algorithms

Winter 2020

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 497: Advanced Topics in Theory+X

Fall 2019

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI 496: Graduate Complexity

Spring 2019

• COMP_SCI 212: Mathematical Foundations of Computer Science
• COMP_SCI 336: Design & Analysis of Algorithms
• COMP_SCI  396/496: Approximation Algorithms
• COMP_SCI 496: Lattices in Computer Science
• COMP_SCI 496: Mathematical Toolkit
• COMP_SCI 497: Advanced Topics in Computational Learning Theory

Winter 2019

• EECS 336: Design & Analysis of Algorithms
• EECS 396/496: Computational Geometry
• EECS 496: Graduate Algorithms
• EECS 496: Computational Learning Theory

Fall 2018

• EECS 212: Mathematical Foundations of Computer Science
• EECS 335: Introduction to the Theory of Computation
• EECS 496: Mechanism Design

Spring 2018

• EECS 212: Mathematical Foundations of Computer Science
• EECS 336: Design & Analysis of Algorithms
• EECS  395/495: Computational Learning Theory
• EECS 495: Topics in Beyond Worst-Case Analysis

Winter 2018

• EECS 336: Design & Analysis of Algorithms
• EECS 495 : Graduate Algorithms

Fall 2017

• EECS 335: Introduction to the Theory of Computation
• EECS 336: Design & Analysis of Algorithms
• EECS 495: Analytical Methods in Theoretical Computer Science
• EECS 495: Mechanism Design

Spring 2017

• EECS  495: Approximation Algorithms

Winter 2017

• EECS 395/495: Bioinformatics

Spring 2016

• EECS 336: Design & Analysis of Algorithms
• EECS  395: Computational Learning Theory

Winter 2016

• EECS 212 : Mathematical Foundations of Computer Science.
• EECS 335: Introduction to the Theory of Computation
• EECS 495 : Graduate Algorithms

Fall 2015

• EECS 212 : Mathematical Foundations of Computer Science.
• EECS 336: Design & Analysis of Algorithms
• EECS 395/495: Bioinformatics

Here are a list of theory courses that have been offered in previous years and that are likely to be offered regularly.

• Computational Complexity
• Derandomization
• Probabilistic Method
• Introduction to Cryptography
• Kolmogorov Complexity
• Introduction to Algorithms
• Algorithmic Mechanism Design
• Randomized Algorithms
• Algorithmic and Economic Aspects of Social Networks
• Combinatorial Optimization
• Algorithmic Research for E-Commerce