# Information and Data Sciences

**IDS 9. Introduction to Information and Data Systems Research.** *1 unit (1-0-0); second term. *This course will introduce students to research areas in IDS through weekly overview talks by Caltech faculty and aimed at first-year undergraduates. Others may wish to take the course to gain an understanding of the scope of research in computer science. Graded pass/fail. Instructor: Ralph.

**ACM/IDS 101 ab. Methods of Applied Mathematics.** *12 units (4-0-8). *For course description, see Applied and Computational Mathematics.

**ACM/IDS 104. Applied Linear Algebra. ***9 units (3-1-5).* For course description, see Applied and Computational Mathematics.

**CMS/ACM/IDS 107. Linear Analysis with Applications.** *12 units (3-3-6). * For course description, see Computing and Mathematical Sciences.

**CMS/ACM/IDS 113. Mathematical Optimization. ***12 units (3-3-6). *For course description, see Computing and Mathematical Sciences.

**ACM/CS/IDS 114. Parallel Algorithms for Scientific Applications.** *9 units (3-0-6). *For course description, see Applied and Computational Mathematics.

**ACM/EE/IDS 116. Introduction to Probability Models. ***9 units (3-1-5). *For course description, see Applied and Computational Mathematics.

**CMS/ACM/EE/IDS 117. Probability and Random Processes. ***12 units (3-0-9). *For course description, see Computation and Mathematical Sciences.

**CS/IDS 121. Relational Databases. ***9 units (3-0-6). *For course description, see Computer Science.

**CS/IDS 122. Database System Implementation. ***9 units (3-3-3). *For course description, see Computer Science.

**EE/Ma/CS/IDS 127. Error-Correcting Codes. ***9 units (3-0-6). *For course description, see Electrical Engineering.

**EE/Ma/CS/IDS 136. Topics in Information Theory.** *9 units (3-0-6). *For course description, see Electrical Engineering.

**CMS/CS/IDS 139. Analysis and Design of Algorithms. ***12 units (3-0-9). *For course description, see Computation and Mathematical Sciences.

**CS/IDS 142. Distributed Computing. ***9 units (3-0-6). *For course description, see Computer Science.

**CS/EE/IDS 143. Communication Networks.** *9 units (3-3-3).* For course description, see Computer Science.

**CMS/CS/EE/IDS 144. Networks: Structure & Economics. ***12 units (3-3-6).* For course description, see Computing and Mathematical Sciences.

**Ma/ACM/IDS 144 ab. Probability. ***9 units (3-0-6)*. For course description, see Mathematics.

**CS/IDS 150. Probability and Algorithms. ***9 units (3-0-6). *For course description, see Computer Science.

**CS/IDS 153. Current Topics in Theoretical Computer Science. ***9 units (3-0-6).* For course description, see Computer Science.

**ACM/IDS 154. Inverse Problems and Data Assimilation. ***9 units (3-0-6).* For course description, see Applied and Computational Mathematics.

**CMS/CS/CNS/EE/IDS 155. Machine Learning & Data Mining.** *12 units (3-3-6).* For course description, see Computing and Mathematical Sciences.

**ACM/CS/IDS 157. Statistical Inference.** *9 units (3-2-4). *For course description, see Applied and Computational Mathematics.

**ACM/CS/EE/IDS 158. Mathematical Statistics.** *9 units (3-0-6).* For course description, see Applied and Computational Mathematics.

**CS/CNS/EE/IDS 159. Advanced Topics in Machine Learning.** *9 units (3-0-6).* For course description, see Computer Science.

**EE/CS/IDS 160. Fundamentals of Information Transmission and Storage.** *9 units (3-0-6). *For course description, see Electrical Engineering.

**CS/CNS/EE/IDS 165. Foundations of Machine Learning. ***12 units (3-3-6).* For course description, see Computer Science.

**EE/CS/IDS 167. Introduction to Data Compression and Storage.*** 9 units (3-0-6).* For course description, see Electrical Engineering.

**ACM/EE/IDS 170. Mathematics of Signal Processing. ***12 units (3-0-9). *For course description, see Applied and Computational Mathematics.

**CS/IDS 178. Numerical Algorithms and their Implementation. ***9 units (3-3-3). *For course description, see Computer Science.

**IDS 197. Undergraduate Reading in the Information and Data Sciences. ***Units are assigned in accordance with work accomplished; first, second, third terms. Prerequisites: Consent of supervisor is required before registering.* Supervised reading in the information and data sciences by undergraduates. The topic must be approved by the reading supervisor and a formal final report must be presented on completion of the term. Graded pass/fail. Instructor: Staff.

**IDS 198. Undergraduate Projects in Information and Data Sciences. ***Units are assigned in accordance with work accomplished; first, second, third terms. Prerequisites: Consent of supervisor is required before registering. *Supervised research in the information and data sciences. The topic must be approved by the project supervisor and a formal report must be presented upon completion of the research. Graded pass/fail. Instructor: Staff.

**IDS 199. Undergraduate thesis in the Information and Data Sciences. ***9 units (1-0-8); first, second, third terms. Prerequisites: instructor’s permission, which should be obtained sufficiently early to allow time for planning the research.* Individual research project, carried out under the supervision of a faculty member and approved by the option representative. Projects must include significant design effort and a written Report is required. Open only to upperclass students. Not offered on a pass/fail basis. Instructor: Staff.

**ACM/IDS 204. Topics in Linear Algebra and Convexity. ***12 units (3-0-9). *For course description, see Applied and Computational Mathematics.

**ACM/IDS 213. Topics in Optimization. ***9 units (3-0-6). *For course description, see Applied and Computational Mathematics.

**ACM/IDS 216. Markov Chains, Discrete Stochastic Processes and Applications. ***9 units (3-0-6). *For course description, see Applied and Computational Mathematics.

**ACM/EE/IDS 217. Advanced Topics in Stochastic Analysis. ***9 units (3-0-6).* For course description, see Applied and Computational Mathematics.