Related Pages 
Fall Term 2021-22
Applied & Computational Mathematics
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| ACM 80a(Letter Grade) | Undergraduate Thesis | Staff | - | - |
| ACM 81a(Letter Grade or Pass/Fail) | Undergraduate Projects in Applied and Computational Mathematics | Staff | - | - |
| ACM/IDS 101a(4-4-4)(Letter Grade or Pass/Fail) | Methods of AppliedMathematics | Bruno | TTh 2:30-4:25 | 104 ANB |
| ACM/IDS 104(3-1-5)(Letter Grade or Pass/Fail) | Applied Linear Algebra | Zuev | TTh 10:30-11:55 | Remote |
| ACM/EE 106a(3-0-9)(Letter Grade or Pass/Fail) | Introductory Methods of Computational Mathematics | Hou | MW 1:00-2:30 | Remote |
| CMS/ACM/IDS 107(3-0-9)(Letter Grade or Pass/Fail) | Linear Analysis with Applications | Stuart | TTh 9:00-10:25 | 213 ANB |
| ACM/EE/IDS 116(3-1-5)(Letter Grade or Pass/Fail) | Introduction to Probability Models | Zuev | TTh 9:00-10:25 | Remote |
| ACM/CMS 117(3-0-9)(Letter Grade or Pass/Fail) | Probability Theory and Stochastic Processes | Tropp | M 2:30-4:00TTh 10:30-12:00 | 213 ANB |
| CMS/ACM/EE 122(3-0-9) | Mathematical Optimization | Chandrasekaran | MWF 10:30-11:55 | 105 ANB |
| ACM/IDS 154(3-0-6)(Letter Grade or Pass/Fail) | Inverse Problems and Data Assimilation | Stuart | TTh 1:00-2:25 | Remote |
| ACM 190(Letter Grade or Pass/Fail) | Reading and Independent Study | Staff | - | - |
| ACM 300(Pass/Fail) | Research in Applied and Computational | Staff | - | - |
Control & Dynamical Systems
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CDS 90a(Letter Grade)(0-0-9) | Senior Thesis in Control and Dynamical Systems | Staff | - | - |
| CDS 131(3-0-6)(Letter Grade) | Linear Systems Theory | Chung | MWF 2:00-2:55 | 105 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/ACM/IDS 107(3-0-9)(Letter Grade or Pass/Fail) | Linear Analysis with Applications | Stuart | TTh 9:00-10:25 | Remote |
| CMS/ACM 117(3-0-9)(Letter Grade or Pass/Fail) | Probability Theory and Stochastic Processes | Tropp | MTTh 1:00-3:25 | 104 ANB |
| CMS/ACM/EE 122(3-0-9) | Mathematical Optimization | Chandrasekaran | MWF 10:30-11:55 | 104 ANB |
| CMS 290a(1-0-0)(Pass/Fail) | Computing & Mathematical Sciences Colloquium | Hou | M 4:00-4:55 | Remote |
| CMS 300(Pass/Fail) | Research in Computing & Mathematical Sciences | Faculty | - | - |
Computer Science
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CS 1(3-4-2)(Pass/Fail) | Intermediate Computer Programming | Hovik | MWF 2:00-2:55 | Remote |
| CS 1x(2-2-2)(Pass/Fail) | Intermediate Computer Programming | Vanier | OM T 9/28 7:00-8:00pm | 105 ANB |
| CS 9(1-0-0)(Pass/Fail) | Introduction to Computer Science Research | Low | Th 12:00-12:55 | Remote |
| CS 11(0-3-0)(Pass/Fail) | Computer Language Lab(CS 1 or instructor's permission is required / Sec 1: C / Sec 10: ICPC (cancelled) / Sec 11: cancelled, offered as CS 12, Sec 1 / Sec 12: Projects / Sec 13: cancelled, offered as CS 12, Sec 2: Technical Interviewing / Sec 15: Rust) | Vanier/Blank | CS11: OM, M 9:00-9:55CS11 Section 10: OM, M 9:00-9:55 | Beckman Auditorium |
| CS 12(0-3-0)Pass/Fail | Student-Taught Topics in Computing(Sec 1: TensorFlow / Sec 2: Technical Interviewing) | Vanier/Blank/Ralph | OM (Section 2, Technical Interviewing), M 8:00-9:00 | Sec 1:105 ANBSec 2:Beckman Auditorium |
| CS 24(3-3-3)(Letter Grade or Pass/Fail) | Introduction to Computing Systems | Blank | MWF 2:00-2:55 | Beckman Auditorium |
| CS 80(Letter Grade) | Undergraduate Thesis | Faculty | - | - |
| CS 81a(Pass/Fail) | Undergraduate Projects in Computer Science | Faculty | - | - |
| CS 90(Pass/Fail) | Undergraduate Research in Computer Science | Faculty | - | - |
| CS 101(Letter Grade) | Special Topics in Computer Science: Projects in Machine Learning | Bouman | OM M 10:00-10:55 | 105 ANB |
| CS 101, Section 2(3-0-6) | Special Topics in Computer Science: Networks of Relations | Cook | TTh 1:00-2:25 | - |
| CS 102a | Seminar in Computer Science | Faculty | - | - |
| CS 103a | Reading in Computer Science | Faculty | - | - |
| CS 111(0-3-0) | Graduate Programming Practicum(For graduate students only / Sec 1: C / Sec 11: Special Topics / Sec 12: Projects / Sec 13: Interview Preparation / Sec 15: Rust) | Vanier/Blank | OM M 9:00-9:55pm | 105 ANB |
| CS/IDS 142(3-2-4)(Letter Grade or Pass/Fail) | Distributed Computing | Chandy | MWF 1:00-1:55 | Remote |
| CS/IDS 150a(3-0-6)(Letter Grade or Pass/Fail) | Probability and Algorithms | Schulman | MWF 10:00-10:55 | North Tent |
| CS 152(3-0-9)(Letter Grade or Pass/Fail) | Introduction to Cryptography | Vidick | TTh 10:30-11:55 | South Tent |
| CS/CNS/EE 156a(3-1-5)(Letter Grade or Pass/Fail) | Learning Systems | Abu-Mostafa | OM 9/27 4:00-4:55 Beckman Auditorium | Remote |
| CS/CNS 171(Letter Grade or Pass/Fail) | Computer Graphics Laboratory | Barr | MWF 3:00-3:55 | 105 ANB |
| CS 180 | Master's Thesis Research | Faculty | - | - |
| CS 280(Pass/Fail) | Research in Computer Science | Faculty | - | - |
| CS 286(3-0-3)(Pass/Fail) | Seminar in Computer Science: Research seminar on advanced topics in quantum computing | Mahadev | F 1:00-4:00 | 213 ANB |
| CS 287 | Center for the Mathematics of Information Seminar | Staff | T 4:00-4:55 | 105 ANB |
Information and Data Systems
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| IDS/Ec/PS 126(3-0-6) | Applied Data Analysis | Katz | MWF 10:30-11:55 | Baxter Lecture Hall |
| 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 2021-22
Applied & Computational Mathematics
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| ACM 80b(Letter Grade)(9) | Undergraduate Thesis | Staff | - | - |
| ACM 81b(Letter Grade or Pass/Fail) | Undergraduate Projects in Applied and Computational Mathematics | Staff | - | - |
| ACM 95/100a(Letter Grade or Pass/Fail)(4-0-8) | Introductory Methods of Applied Mathematics | Zuev | - | - |
| ACM/IDS 101b(Letter Grade or Pass/Fail)(4-4-4) | Methods of AppliedMathematics | Bruno | - | - |
| ACM 105(3-0-6) | Applied Real and Functional Analysis | Leong | - | - |
| ACM/EE 106b(Letter Grade or Pass/Fail)(3-0-9) | Introductory Methods of Computational Mathematics | Hou | - | - |
| ACM 118(3-0-9) | Stochastic Processes and Regression | Owhadi | - | - |
| ACM 190(Pass/Fail) | Reading and Independent Study | Staff | - | - |
| ACM/IDS 204 | Topics in Linear Algebra and Convexity: Matrix Analysis | Tropp | - | - |
| ACM/IDS 216(3-0-6) | Markov Chains, Discrete Stochastic Processes and Applications | Owhadi | - | - |
| ACM 300(Pass/Fail) | Research in Applied & Computational Mathematics | Staff | - | - |
Control & Dynamical Systems
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CDS 90b(Letter Grade)(0-0-9) | Senior Thesis in Control and Dynamical Systems | Staff | - | - |
| CDS 112(3-0-6) | Optimal Control and Estimation | Murray | - | - |
| CDS 190(Pass/Fail) | Independent Work in Control and Dynamical Systems | Staff | - | - |
| CDS 231(3-2-4) | Robust Control Theory | Doyle | - | - |
| CDS 232 | Nonlinear Dynamics | Ames | - | - |
| CDS 300b(Pass/Fail) | Research in Control and Dynamical Systems | Faculty | - | - |
Computing and Mathematical Sciences
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CMS/CS/IDS 139(Letter Grade or Pass/Fail)(3-0-9) | Analysis and Design of Algorithms | Vidick | - | - |
| CMS/CS/EE/IDS 144(Letter Grade or Pass/Fail)(3-4-5) | Networks: Structure & Economics | Wierman | - | - |
| CMS/CNS/EE/IDS 155(Letter Grade or Pass/Fail)(3-3-6) | Machine Learning and Data Mining | Yue | - | - |
| CMS 290b(Pass/Fail)(1-0-0) | Computing & Mathematical Sciences Colloquium | Hou | - | - |
| CMS 300(Pass/Fail) | Research in Computing & Mathematical Sciences | Staff | - | - |
Computer Science
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CS 2(2-4-3) | Introduction to Programming Methods | Blank | - | - |
| CS 11(Pass/Fail)(0-3-0) | Computer Language Lab | Hovik/Vanier | - | - |
| CS 12(0-3-0)Pass/Fail | Student-Taught Topics in Computing | - | - | - |
| CS 19b(Pass/Fail)(2-0-0) | Introduction to Computer Science in Industry | Ralph | - | - |
| CS 21(3-0-6) | Decidability and Tractability | Umans | - | - |
| CS 22(3-0-6) | Data Structures and Parallelism | Blank | - | - |
| CS 42(Pass/Fail)(2-2-2) | Computer Science Education in K14 Settings | Ralph/Wierman | - | - |
| CS 80(Letter Grade)(9) | Undergraduate Thesis | Faculty | - | - |
| CS 81a(Pass/Fail) | Undergraduate Laboratory in Computer Science | Faculty | - | - |
| CS 90(Pass/Fail) | Undergraduate Research in Computer Science | Faculty | - | - |
| CS 102b | Seminar in Computer Science | Faculty | - | - |
| CS 103a | Reading in Computer Science | Faculty | - | - |
| CS 111(0-3-0) | Graduate Programming Practicum | Hovik/Vanier | - | - |
| CS 118(3-3-3) | Logic Model Checking for Formal Software Verification | Holzmann | - | - |
| CS/IDS 121(3-0-6) | Relational Databases | Hovik | - | - |
| CS 130(3-3-3) | Software Engineering | Pinkston | - | - |
| CS/EE 146(3-3-3) | Control and Optimization of Networks | Low | - | - |
| CS/CNS/EE/IDS 165(3-3-6) | Foundations of Machine Learning and Statistical Inference | Anandkumar | - | - |
| CS/ACM 177a(3-3-3) | Discrete Differential Geometry: Theory and Applications | Schröder | - | - |
| CS 180(Pass/Fail) | Master's Thesis Research | Faculty | - | - |
| CS 280(Pass/Fail) | Research in Computer Science | Faculty | - | - |
| CS 287 | Center for the Mathematics of Information Seminar | Staff | - | - |
Information and Data Systems
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| EE/CS/IDS 160(3-0-6) | Fundamentals of Information Transmission and Storage | Kostina | - | - |
| 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(Letter Grade)(1-0-8) | Undergraduate Thesis in the Information and Data Sciences | Staff | - | - |
Spring Term 2021-22
Applied & Computational Mathematics
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| ACM 11 (Letter Grade or Pass/Fail) (2-2-2) | Introduction to Matlab and Mathematica | Qian | M 1:00-3:00 | 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 (Letter Grade or Pass/Fail) (4-0-8) | Introductory Methods of Applied Mathematics | Meiron | MWF 11:00-12:15 | BLH |
| IDS/ACM/CS 157 (Letter Grade or Pass/Fail) (3-2-4) | Statistical Inference | Zuev | TTh 9:00-10:25 | BLH |
| ACM 190 (Letter Grade or Pass/Fail) | Reading and Independent Study | Staff | - | - |
| ACM/IDS 213 (Letter Grade or Pass/Fail)(3-0-6) | Topics in Optimization | Qian | MW 10:00-11:30 | 213 ANB |
| ACM 270 (Letter Grade) | Advanced Topics in Applied & Computational Mathematics: Mathematics of Data Science | Leong | TTh 10:30-12:00 | 106 ANB |
| ACM 300 (Pass/Fail) | Research in Applied & Computational Mathematics | Staff | - | - |
Control & Dynamical Systems
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CDS 90c (Letter Grade) (0-0-9) | Senior Thesis in Control and Dynamical Systems | Murray | - | - |
| CDS 110 (Letter Grade) (3-3-3) | Introduction to Feedback Control Systems (Taught concurrently with ChE105) | Seinfeld | MWF 1:00-1:55 | 106 Spalding Lab |
| CDS 141 (Pass/Fail) (3-2-4) | Network Control Systems | Doyle | TTh 1:00-2:25 | 106 ANB |
| CDS 190 (Pass/Fail) | Independent Work in Control and Dynamical Systems | Staff | - | - |
| CDS 233 (3-0-6) | Nonlinear Control | Niemeyer | TTh 2:30-3:55 | 104 ANB |
| CDS 300c | Research in Control and Dynamical Systems | Burdick, Doyle, Goentoro, Beck, Dickinson, Murray, Owhadi, Quartz, Elowitz, Desbrun, Ortiz, Adolphs, Siapas, Ames, Chung | - | - |
Computing and Mathematical Sciences
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CMS 290c (Pass/Fail) (1-0-0) | Computing & Mathematical Sciences Colloquium | Hou | - | - |
| CMS 300 (Pass/Fail) | Research in Computing & Mathematical Sciences | Staff | - | - |
Computer Science
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| CS 3 (Letter Grade) (1-6-2) | Introduction to Software Design | Blank | M 1:00-1:55 + Lab Tuesdays 1:00-6:55 | Beckman Institute |
| CS 12 (Pass/Fail) (0-3-0) | Student-Taught Topics in Computing | Faculty | OM M 3/28 8:00-9:00PM | 105 ANB |
| CS 38 (Letter Grade or Pass/Fail) (3-0-6) | Algorithms | Schroeder | TTh 10:30-11:55 | 119 KRK |
| CS 42 (Pass/Fail) (2-2-2) | Computer Science Education in K14 Settings | Ralph/Wierman | F 12:00-2:55 | 106 ANB |
| CS 80 (Letter Grade) | Undergraduate Thesis | Faculty | - | - |
| CS 81c (Pass/Fail) | Undergraduate Laboratory in Computer Science | Faculty | - | - |
| CS 90 (Pass/Fail) | Undergraduate Research in Computer Science | Faculty | - | - |
| CS 101 (Pass/Fail) (3-0-3) | Special Topics in Computer Science: Topics in theoretical computer science and quantum computing | Mahadev | F 1:00-4:00 | 213 ANB |
| CS 102c (Letter Grade or Pass/Fail) | Seminar in Computer Science | Faculty | - | - |
| CS 103a (Pass/Fail) | Reading in Computer Science | Faculty | - | - |
| CS 115 (Letter Grade or Pass/Fail) (3-4-2) | Functional Programing | Vanier | MWF 2:00-2:55 | 105 ANB |
| CS 124 (Letter Grade or Pass/Fail) (3-6-3) | Operating Systems | Pinkston | MWF 1:00-1:55 | 105 ANB |
| CS 131 (Letter Grade or Pass/Fail) (3-0-6) | Programming Languages | Vanier | MWF 3:00-3:55 | 104 ANB |
| CS 132 (Letter Grade or Pass/Fail) (3-0-6) | Web Development | Hovik | TTh 10:30-12:00 | 105 ANB |
| CS 137 (Letter Grade ) (2-9-1) | Algorithms in the Real World | Blank | OM M 3/28 8:00-9:00PM | 105 ANB |
| CS 138 (Letter Grade or Pass/Fail) (3-0-6) [Ref. CS 38 (UG version)] | Computer Algorithms | Schroeder | TTh 10:30-11:55 | 119 KRK |
| CS/EE 145 (Letter Grade or Pass/Fail) (0-0-9) | Projects in Networking | Wierman | OM M 3/28 10:00-11:00 | 105 ANB |
| CS/Ec 149 (3-0-6) | Algorithmic Economics | Sandormirskiy | MWF 10:00-10:55 | 127 BAX |
| CS/IDS 153 (Letter Grade or Pass/Fail) (3-0-6) | Current Topics in Theoretical Computer Science | Umans/Schulman | TTh 1:00-2:25 | 213 ANB |
| CS/CNS/EE 156b (Letter Grade or Pass/Fail) (3-1-5) | Learning Systems | Abu-Mostafa | TTh 2:30-4:00 | B270 MRE |
| CS/CNS/EE/IDS 159 (Letter Grade or Pass/Fail) (3-0-6) | Advanced Topics in Machine Learning | Yue | TTh 2:30-3:55 | 105 ANB |
| CS 163 (Letter Grade or Pass/Fail) (3-0-3) | Making Data Visual | Slavick | W 7:00-9:55PM | 128 Baxter |
| CS/EE/IDS 166 (Letter Grade or Pass/Fail) (3-3-6) | Computational Cameras | Bouman | TTh 1:00-2:30 | 104 ANB |
| CS 179 (Letter Grade or Pass/Fail) (3-3-3) | GPU Programming | Barr | MWF 3:00-3:55 | 105 ANB |
| CS 180 (Pass/Fail) | Master's Thesis Research | Faculty | - | - |
| CS 280 (Pass/Fail) | Research in Computer Science | Faculty | - | - |
| CS 287 (Pass/Fail) | Center for the Mathematics of Information Seminar | Staff | T 4:00-4:55 | 105 ANB |
Information and Data Systems
| Course (Units/Grade) | Subject | Instructor | Time | Room |
|---|---|---|---|---|
| IDS/ACM/CS 157 (Letter Grade or Pass/Fail) (3-2-4) | Statistical Inference | Zuev | TTh 9:00-10:30 | BHL |
| 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 (Letter Grade) (1-0-8) | Undergraduate Thesis in the Information and Data Sciences | Staff | - | - |