Course schedules for upcoming terms are subject to change up to ten weeks before the term begins. Please check this page again to confirm times and locations. [Key to abbreviations]
Fall Term 2024-25
Applied & Computational Mathematics
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
ACM 80a (9) (Letter Grade) |
Undergraduate Thesis | Staff | - | - |
ACM 81a (Letter Grade or Pass/Fail) |
Undergraduate Projects in Applied and Computational Mathematics | Staff | - | - |
ACM/EE 106a (3-0-9) (Letter Grade or Pass/Fail) |
Introductory Methods of Computational Mathematics | Hou | TTh 1:00-2:25 | 104 ANB |
ACM/EE/IDS 116 (3-1-5) (Letter Grade or Pass/Fail) |
Introduction to Probability Models | Zuev | TTh 9:00-10:25 | 125 KRK |
ACM/IDS 101a (4-4-4) (Letter Grade or Pass/Fail) |
Methods of Applied Mathematics | Bruno | MW 10:00-11:55 | 213 ANB |
ACM/IDS 104 (3-1-5) (Letter Grade or Pass/Fail) |
Applied Linear Algebra | Zuev | TTh 10:30-11:55 | 125 KRK |
ACM 190 (Pass/Fail) | Reading and Independent Study | Staff | - | - |
ACM 300 (Pass/Fail) | Research in Applied and Computational Mathematics | Staff | - | - |
Control & Dynamical Systems
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CDS 90a (0-0-9) (Letter Grade) |
Senior Thesis in Control and Dynamical Systems | Staff | - | - |
CDS 110 (3-3-3) (Letter Grade or Pass/Fail) |
Introduction to Feedback Control Systems | Mazumdar | TTh 10:30-11:55 | 213 ANB |
CDS 190 (Pass/Fail) |
Independent Work in Control and Dynamical Systems | Staff | - | - |
CDS 300a (Pass/Fail) |
Research in Control and Dynamical Systems | Staff | - | - |
Computing and Mathematical Sciences
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CMS 9 (1-0-0) (Pass/Fail) |
Introduction to Computer Science Research | Low | Th 12:00-12:55 | 105 ANB |
CMS/ACM 117 (3-0-9) (Letter Grade or Pass/Fail) |
Probability Theory and Computational Mathematics | Tropp | MW 2:00-3:55 | 213 ANB |
CMS/ACM/EE 122 (4-0-8) (Letter Grade or Pass/Fail) |
Mathematical Optimization | Chandrasekaran | MW 10:00-11:55 | 105 ANB |
CMS/ACM/IDS 107 (3-0-9) (Letter Grade or Pass/Fail) |
Linear Analysis with Applications | Stuart | TTh 9:00-10:25 | 213 ANB |
CMS 290a (1-0-0) (Pass/Fail) |
Computing and Mathematical Sciences Colloquium | Hoffmann | M 4:00-4:55 | 105 ANB |
CMS 300 | Research in Computing and Mathematical Sciences | Staff | - | - |
Computer Science
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CS 1 (3-4-2) (Pass/Fail) |
Introduction to Computer Programming | Blank / Vanier | MWF 2:00-2:55 |
Beckman Institute Auditorium |
CS 1x (2-2-2) (Pass/Fail) |
Intermediate Computer Programming | Vanier | W 3:00-3:55 | 104 ANB |
CS 11/111 (0-3-0) (Pass/Fail) |
011: Computer Language Lab / 111: Graduate Programming Practicum | Hovik | OM M 9/30 9:00-10:00pm | 105 ANB |
CS 12 (0-3-0) (Pass/Fail) |
Student-Taught Topics in Computing | Staff |
OM M 9/30 7:00-8:00pm |
104 ANB |
CS 19a (1-0-1) (Pass/Fail) |
Introduction to Computer Science in Industry | Ralph | M 12:00-12:55 | 105 ANB |
CS 24 (3-3-3) (Letter Grade or Pass/Fail) |
Introduction to Computing Systems | Blank | MWF 11:00-11:55 | Beckman Institute |
CS 80a (Pass/Fail) |
Undergraduate Thesis | Staff | - | - |
CS 81a (Pass/Fail) |
Undergraduate Projects in Computer Science | Staff | - | - |
CS 90 (Pass/Fail) |
Undergraduate Reading in Computer Science | Staff | - | - |
CS 132 | Web Development | Hovik | TTh 1:00-2:30 | 314 ANB |
CS 152 (3-0-9) (Letter Grade of Pass/Fail) |
Introduction to Crypotography | Mahadev | MW 1:00-2:25 | 104 ANB |
CS 163 (Letter Grade) |
Special Topics in Computer Science: Projects in Machine Learning | Bouman | OM M 9/30 10:00-11:00 | 104 ANB |
CS 164 (3-0-6) (Letter Grade) |
Compilers | Vanier | MWF 11:00-11:55 | 104 ANB |
CS/CNS 171 (3-6-3) (Letter Grade or Pass/Fail) |
Computer Graphics Laboratory | Barr | MWF 3:00-3:55 | 105 ANB |
CS/CNS/EE 156a (3-1-5) (Letter Grade or Pass/Fail) |
Learning Systems | Abu-Mostafa |
OM M 9/30 4:00-5:00pm (Baxter Lecture Hall) TTh 2:30-3:55 |
Baxter Lecture Hall |
CS/IDS 150a (3-0-6) (Letter Grade or Pass/Fail) |
Probability and Algorithms | Schulman | MWF 10:00-10:55 | 314 ANB |
CS/IDS 153 (3-0-6) (Letter Grade or Pass/Fail) |
Current Topics in Theoretical Computer Science | Umans | TTh 1:00-2:25 | 213 ANB |
CS/EE/IDS 143 (Letter Grade or Pass/Fail) |
Networks: Algorithms & Architecture | Wierman | TTh 10:30-11:55 | 105 ANB |
CS 180 (Pass/Fail) |
Master's Thesis Research | Faculty | - | - |
CS 280 (Pass/Fail) |
Research in Computer Science | Faculty | - | - |
Information and Data Systems
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
IDS/Ec/PS 126 (3-0-6) (Letter Grade) |
Applied Data Analysis | Katz | MW 10:30-11:55 | - |
IDS 197 (Pass/Fail) |
Undergraduate Reading in the Information and Data Sciences | Staff | - | - |
IDS 198 (Pass/Fail) |
Undergraduate Projects in Information and Data Sciences | Staff | - | - |
IDS 199 (1-0-8) (Letter Grade) |
Undergraduate Thesis in the Information and Data Sciences | Staff | - | - |
Winter Term 2024-25
Applied & Computational Mathematics
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
ACM 80b | Undergraduate Thesis | Staff | - | - |
ACM 81b | Undergraduate Projects in Applied and Computational Math | Staff | - | - |
ACM 95/100a | Introductory Methods of Applied Mathematics | Zuev | MWF 11:00-12:15 | 125 KRK |
ACM 118 | Stochastic Processes and Regression | Owhadi | MW 1:00-2:25 | 104 ANB |
ACM 190 | Reading and Independent Study | Staff | - | - |
ACM 256 | Special Topics in Applied Mathematics | Hoffmann | MW 10:00-11:25 | 104 ANB |
ACM 300 | Research in Applied and Computational Mathematics | Staff | - | - |
ACM/EE 106b | Introductory Methods of Computational Mathematics | Hou | TTh 1:00-2:25 | 104 ANB |
ACM/IDS 101b | Methods of Applied Mathematics | Bruno | MW 10:00-11:55 | 213 ANB |
ACM/IDS 154 | Inverse Problems and Data Assimilation | Carlson | TTh 10:30-11:55 | 213 ANB |
ACM/IDS 216 | Markov Chains, Discrete Stochastic Processes and Applications | Owhadi | TTh 9:00-10:25 | 104 ANB |
Control & Dynamical Systems
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CDS 90b | Senior Thesis in Control and Dynamical Systems | Ames | - | - |
CDS 190 | Independent Work in Control and Dynamical Systems | Staff | ||
CDS 131 | Linear Systems Theory | Doyle | MW 1:00-2:25 | 314 ANB |
CDS 232 | Nonlinear Dynamics | Ames | MWF 4:00-5:25 | 135 GTL |
CDS 245 | Data-driven Control | Chung | TTh 10:30-11:55am | 104 ANB |
CDS 300b | Research in Control and Dynamical Systems | Staff | - | - |
Computing and Mathematical Sciences
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CMS 290b | Computing and Mathematical Sciences Colloquium | Hoffmann | M 4:00-4:55 | 105 ANB |
CMS 300 | Research in Computing and Mathematical Sciences | Staff | - | - |
CMS/CS/CNS/EE 155 | Machine Learning & Data Mining | Yue | TTh 2:30-3:55 | Beckman Institute Auditorium |
CMS/CS/EE/IDS 144 | Networks: Structure & Economics | Mazumdar | MWF 2:30-3:55 | 104 ANB |
Computer Science
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CS 2 |
Introduction to Programming Methods: (Maximum enrollment: 16 students per section) |
Blank | MWF 2:00-2:55 | Beckman Institute Auditorium |
CS 4 | Fundamentals of Computer Programming | Vanier | MWF 3:00-3:55 | Beckman Institute Auditorium |
CS 11 / 111 | 011: Computer Language Lab CS 1 or instructor's permission is required. / Sec 1: C | Vanier | OM M 1/6 9:00-10:00pm | 105 ANB |
CS 12 |
Student-Taught Topics in Computing Sec 9: Single Board Computers in Research |
Blank | OM M 1/6 8:00-9:00pm | 104 ANB |
CS 21 | Decidability and Tractability | Umans | MWF 1:00-1:55 | 105 ANB |
CS 42 | Computer Science Education in K14 Settings | Ralph/Wierman | W 2:00-3:00 | 121 ANB |
CS 80b | Undergraduate Thesis | Staff | - | - |
CS 81b | Undergraduate Projects in Computer Science | Staff | - | - |
CS 90 | Undergraduate Reading in Computer Science | Staff | - | - |
CS 101 | Section 02: Special Topics in Computer Science: Introduction to Computational Social Sciences and Data Science in Python | Tsang | TTh 2:30-4:00 | 314 ANB |
CS 102b | Seminar in Computer Science | Staff | - | - |
CS 103b | Reading in Computer Science | Staff | - | - |
CS 128 | Interactive Theorem Proving | Vanier | MWF 11:00-11:55 | 314 ANB |
CS 130 | Software Engineering | Pinkston | MWF 11:00-11:55 | 105 ANB |
CS 180 | Master's Thesis Research | Staff | - | - |
CS 280 | Research in Computer Science | Staff | - | - |
CS 282b | Reading in Computer Science | Staff | - | - |
CS/CNS/EE/IDS 165 | Foundations of Machine Learning and Statistical Inference | Anandkumar | TTh 1:00-2:25 | 314 ANB |
CS/EE 146 | Control and Optimization of Networks | Low |
T 4:00-5:30 F 1:00-2:30PM |
314 ANB |
CS/IDS 121 | Relational Databases | Hovik | MWF 10:00-10:55 | 105 ANB |
CS/IDS 162 |
Data, Algorithms and Society Taught concurrently with VC 162 / Maximum enrollment: 15 students between VC 162 and CS/IDS 162 / Instructor permission required to add [Apply] |
Ralph/Mushkin | TTh 2:30-3:55 | 104 ANB |
CS/IDS 172 | Distributed Computing | Chandy | TTh 1:00-2:25 | 105 ANB |
Information and Data Systems
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
IDS 197 | Undergraduate Reading in the Information and Data Sciences | Staff | - | - |
IDS 198 | Undergraduate Projects in Information and Data Sciences | Staff | - | - |
IDS 199 | Undergraduate Thesis in the Information and Data Sciences | Staff | - | - |
Spring Term 2024-25
Applied & Computational Mathematics
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
ACM 011 (2-2-2) (Letter Grade) | Introduction to Computational Science and Engineering | Carlson | M 2:00-3:55 | 104 ANB |
ACM 80c (Letter Grade) | Undergraduate Thesis | Staff | - | - |
ACM 81c (Letter Grade or Pass/Fail) | Undergraduate Projects in Applied and Computational Mathematics | Staff | - | - |
ACM 95/100b (4-0-8) (Letter Grade or Pass/Fail) | Introductory Methods of Applied Mathematics for the Physical Sciences | Hoffmann/Cao | MWF 11:00-12:15 | Baxter Lecture Hall |
ACM 190 (Letter Grade or Pass/Fail) | Reading and Independent Study | Staff | - | - |
ACM/IDS 204 (3-0-6) (Letter Grade) | Topics in Linear Algebra and Convexity (Matrix Analysis) | Tropp | TTh 10:30-11:55 | 213 ANB |
ACM 270 (3-0-6) (Pass/Fail) | Advanced Topics in Applied & Computational Mathematics: Data-Driven Modeling of Dynamical Systems | Stepaniants | TTh 1:00-2:25 | 104 ANB |
ACM 300 (Pass/Fail) | Research in Applied and Computational Mathematics | Staff | - | - |
Control & Dynamical Systems
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CDS 90c (Letter Grade) | Senior Thesis in Control & Dynamical Systems | Staff | ||
CDS 190 (Letter Grade or Pass/Fail) | Independent Work in Control and Dynamical Systems | Staff | ||
CDS 212 (Letter Grade or Pass/Fail) | Optimal Control and Estimation | Chung | TTh 10:30-11:55 | 104 ANB |
CDS 231 (Letter Grade or Pass/Fail) | Robust Control Theory | Doyle | TTh 1:00-2:25 | 314 ANB |
CDS 233 (Letter Grade or Pass/Fail) | Nonlinear Control | Ames | MWF 4:00-5:25 | 135 Gates-Thomas |
CDS 300c (Letter Grade or Pass/Fail) | Research in Control and Dynamical Systems | Faculty |
Computing and Mathematical Sciences
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CMS 290c (1-0-0) (Pass/Fail) | Computing and Mathematical Sciences Colloquium | Hoffmann | M 4:00-4:55 | 105 ANB |
CMS 300 (Letter Grade Pass/Fail) | Research in Computing and Mathematical Sciences | Staff | - | - |
Computer Science
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
CS 1 (3-4-2) | Introduction to Computer Programming | Blank / Tsang | 12:00 - 12:55 | 105 ANB |
CS 3 (1-6-2) | Introduction to Software Design | Blank / Tsang | MW 1:00-1:55, Labs: T 10:00am-6:00pm, 106 ANB (section 1-9) | 105 ANB |
CS 11/111 (0-3-0) | Computer Language Lab: C Track | Hovik | OM M 8:00-8:55 pm | 104 ANB |
CS 11/111 (0-3-0) | Computer Language Lab: Rust Track | Vanier | OM M 9:00-9:55 pm | 105 ANB |
CS 38/138 (3-0-6) | Algorithms | Mahadev/Ralph | TTh 1:00-2:25 | 119 KRK |
CS 80c | Undergraduate Thesis | Faculty | - | - |
CS 81c | Undergraduate Projects in Computer Science | Faculty | - | - |
CS 90 | Undergraduate Reading in Computer Science | Faculty | - | - |
CS 101 (3-0-6) | Special Topics in Computer Science: Pedagogy in Computer Science (enrollment by instructor approval only) Cap at 20 students | Blank/Bryant | OM T 7:00-7:55 pm | 106 ANB |
CS 101 (3-0-6) | Special Topics in Computer Science: Introduction to Computational Social Sciences and Data Science in Python | Tsang | TTh 10:30-11:55 | 314 ANB |
CS 102c | Seminar in Computer Science | Staff | - | - |
CS 103c | Reading in Computer Science | Staff | - | - |
CS 115 (3-4-2) | Functional Programming | Vanier | MWF 2:00-2:55 | 105 ANB |
CS 131 (3-0-6) |
Programming Languages maximum enrollment: 30 students // CS 4 (in OCaml) is a hard prerequisite (i.e. CS 4 starting) |
Vanier | MWF 3:00-3:55 | 213 ANB |
CS 132 (3-0-6) | Web Development | Hovik | TTh 10:30-11:55 | 105 ANB |
CS 151 (3-0-9) | Complexity Theory | Umans | TTh 1:00-2:25 | 213 ANB |
CS 179 (3-3-3) | GPU Programming | Barr | MWF 3:00-3:55 | 105 ANB |
CS 180 | Master's Thesis Research | Staff | - | - |
CS 280 | Research in Computer Science | Staff | - | - |
CS 282c | Reading In Computer Science | Staff | - | - |
CS/IDS 150b (3-0-6) | Probability and Algorithms | Schulman | MWF 10:00-10:55 | 314 ANB |
CS/CNS/EE 156B (3-1-5) | Learning Systems | Abu-Mostafa | TTh 2:30-3:55 | B270 MRE |
CS/CNS/EE/IDS 159 (3-0-6) | Advanced Topics in Machine Learning | Yue | TTh 2:30-3:55 | 105 ANB |
CS/EE 145 (0-0-9) | Projects in Networking | Wierman | OM M 10:00-10:55 | 104 ANB |
CS/Ec 149 (3-0-6) | Algorithmic Economics | Neimeyer | MW 2:30-3:55 | - |
Information and Data Systems
Course (Units/Grade) | Subject | Instructor | Time | Room |
---|---|---|---|---|
IDS 197 | Undergraduate Reading in the Information and Data Sciences | Staff | - | - |
IDS 198 | Undergraduate Projects in Information and Data Sciences | Staff | - | - |
IDS 199 | Undergraduate Thesis in the Information and Data Sciences | Staff | - | - |
IDS/ACM/CS 157 (3-2-4) (Letter Grade or Pass/Fail) | Statistical Inference | Zuev | TTh 9:00-10:25 | Baxter Lecture Hall |