Undergraduate Core Requirements

[Updated February 22, 2017 - added OSPSANTG 48 to area 10b and 11a options]

Below is the latest sub-version of the current Core Requirements, known as the Generation 3 Core. In general, students are not bound by changes in requirements that are instituted after they declare. For previous versions of the Core, see Metadata: >> Versions on the right side of this page, or the previous Stanford Bulletins. All major courses must be taken for letter grades unless an approved course is offered satisfactory/no credit only. This is a strict policy. NOTE that all core courses must be passed with a C- or better to complete the major. Students who get lower than a C- in a core course should contact the program director or associate director to discuss whether they should continue in the program.

In order to graduate with a B.S. in Symbolic Systems, a student must complete the following requirements, plus a five-course concentration.  For some sample quarter-by-quarter plans to complete the core, click here. Some of the courses listed below have other courses as prerequisites; students are responsible for completing each course’s prerequisites before they take it.  With the exception of the advanced small seminar requirement, which can be fulfilled by a course taken for one other requirement in either the core or a concentration, courses cannot be used towards more than one area of the core requirements.

The requirements below are effective immediately. Note that the Core previous to this (Versions 11 and earlier) required six-course concentrations. The core described below is quite flexible, and when combined with different concentrations, it allows students to achieve high unit levels in any of our cognate departments.

For assistance with planning a course schedule during your remaining quarters at Stanford, see Sample Schedules for Completing Current Core Requirements.

Note also that not all courses in the list below (or in concentration lists) are being taught presently. Some are not offered this year but may be in the future. We continue to list recently discontinued courses for the benefit of students who have already taken those courses in previous years.

    1. Introductory Core Course.
      • SYMSYS 1. Minds and Machines (same as LINGUIST 35, PHIL 99, PSYCH 35) [NOTE: Students matriculating with the Class of 2018 or later must take SYMSYS 1 prior to declaring a Symbolic Systems major]
    2. Continuous Fundamentals Level 1. Single Variable Calculus (one of the following):
      • 10 units of Advanced Placement Calculus credit
      • All three of the following:
        • MATH 19. Calculus
        • MATH 20. Calculus
        • MATH 21. Calculus
      • Both of the following:
        • MATH 41. Calculus (Accelerated)
        • MATH 42. Calculus (Accelerated)
      • Both of the following:
        • MATH 41A. Calculus (Accelerated), ACE program
        • MATH 42A. Calculus (Accelerated), ACE program
      • Equivalent preparation in Single Variable Calculus, as judged by student
    3. Continuous Fundamentals Level 2. Multivariable Calculus (one of the following):
      • CME 100. Vector Calculus for Engineers (same as ENGR 154)
      • CME 100A. Vector Calculus for Engineers, ACE program
      • MATH 51. Linear Algebra and Differential Calculus of Several Variables
      • MATH 51A. Linear Algebra and Differential Calculus of Several Variables, ACE program
      • MATH 51H. Honors Multivariable Mathematics

NOTE: The following are optional but recommended and may be required for some higher level courses:

      • Additional courses in the Math 50 series
        • MATH 52. Integral Calculus of Several Variables
        • MATH 53. Ordinary Differential Equations with Linear Algebra
      • Or additional courses in the CME 100 series
        • CME 102. Ordinary Differential Equations for Engineers (same as ENGR 155A)
        • CME 104. Linear Algebra and Partial Differential Equations for Engineers (same as ENGR 155B)
    1. Continuous Fundamentals Level 3. Probability and Statistics (one of the following):
      • CS 109. Introduction to Probability for Computer Scientists
      • STATS 116. Theory of Probability
      • STATS 110. Statistical Methods in Engineering and the Physical Sciences
      • MS&E 120. Probabilistic Analysis
      • MS&E 220. Probabilistic Analysis
      • EE 178. Probabilistic Systems Analysis (same as EE 278A)
      • MATH 151. Introduction to Probability Theory
      • CME 106. Introduction to Probability and Statistics for Engineers (same as ENGR 155C)
    2. Discrete Fundamentals.
      1. Computing Level 1 (one of the following):
        • CS 106A. Programming Methodology (same as ENGR 70A)
        • Or equivalent preparation, as judged by student
      2. Computing Level 2 (one of the following):
        • CS 106B. Programming Abstractions (same as ENGR 70B)
        • CS 106X.  Programming Abstractions, Accelerated (same as ENGR 70X)
      3. Logic and the Theory of Computation (one of the following):
        • CS 103.  Mathematical Foundations of Computing
        • PHIL 150. Basic Concepts in Mathematical Logic (same as PHIL 250)
        • PHIL 150E. Logic in Action: A New Introduction to Logic
    3. Technical Depth. Two courses that build on those in requirements 4 an/or 5 above, chosen from the list below (from either the same or different areas). Courses should be chosen in a way that is appropriate/helps prepare for those in a student’s concentration.

Note especially:  students concentrating in HCI, AI, or Computer Music must take CS 107 or 107E (see Area A below). Other concentrations may also restrict the particular courses that can be taken to fulfill this requirement. See concentration lists at http://symsys.stanford.edu/viewing/htmldocument/13690.

      • Area A. Computer Programming
        • CS 107. Computer Organization and Systems, or
        • CS 107E. Computer Systems from the Ground Up
        • note: Only one of the above courses may count toward the Technical Depth requirement
      • Area B: Computational Theory
        • CS 154. Introduction to Automata and Complexity Theory
        • CS 161. Design and Analysis of Algorithms
        • PHIL 151A. Recursion Theory (same as PHIL 251A)
      • Area C. Logic
        • CS 157. Logic and Automated Reasoning
        • PHIL 151. Metalogic (same as PHIL 251)
        • PHIL 152. Computability and Logic (same as PHIL 252)
        • PHIL 154. Modal Logic (same as PHIL 254)
      • Area D. Decision Theory/Game Theory
        • CS 238. Decision Making Under Uncertainty (same as AA 228)
        • ECON 160. Game Theory and Economic Applications
        • ECON 180. Honors Game Theory
        • MS&E 252. Decision Analysis I: Foundations of Decision Analysis
        • POLISCI 152. Introduction to Game Theoretic Methods in Political Science (same as POLISCI 352)
        • POLISCI 356A. Formal Theory I: An Introduction to Game Theory
      • Area E. Probability and Statistics
        • STATS 200. Introduction to Statistical Inference
        • STATS 217. Stochastic Processes
        • CS 228. Probabilistic Graphical Models: Principles and Techniques
        • CS 246. Mining Massive Data Sets
        • MS&E 221. Stochastic Modeling
        • MS&E 226. "Small" Data
    1. Philosophical Foundations Level 1. Introductory Philosophy (one of the following):
      • PHIL 1. Introduction to Philosophy
      • PHIL 2.  Introduction to Moral Philosophy (same as ETHIC SOC20)
      • PHIL 60. Introduction to Philosophy of Science (same as HPS 60)
      • PHIL 102. Modern Philosophy, Descartes to Kant
      • PHIL 135. Existentialism
      • ESF 7. Education as Self-Fashioning: The Transformation of the Self
      • All three of the following SLE courses (must complete all three):
        • SLE 91. Structured Liberal Education
        • SLE 92. Structured Liberal Education
        • SLE 93. Structured Liberal Education
      • THINK 14. From the Closed World to the Infinite Universe: Science, Philosophy and Religion
      • THINK 24. Evil
      • OSPOXFRD 20. Oxford Philosophy: Its Origins and Legends
      • Other introductory courses taught in the Philosophy Department, if approved by the Program Director or Associate Director
    2. Philosophical Foundations Level 2.
      • PHIL 80. Mind, Matter, and Meaning (WIM Course)
    3. Philosophical Foundations Level 3. An advanced undergraduate Philosophy course that lists PHIL 80 as a prerequisite (one of the following):
      • PHIL 106A. Philosophy of Neuroscience (same as PHIL 206A, SYMSYS 206A)
      • PHIL 107B. Plato's Metaphysics and Epistemology
      • PHIL 173B. Metaethics
      • PHIL 175. Philosophy of Law
      • PHIL 180. Metaphysics (same as PHIL 280)
      • PHIL 180A. Realism, Anti-Realism, Irrealism, Quasi-Realism (same as PHIL 280A)
      • PHIL 181. Philosophy of Language (same as PHIL 281)
      • PHIL 182. Advanced Philosophy of Language (same as PHIL 282)
      • PHIL 184. Epistemology (same as PHIL 284)
      • PHIL 186. Philosophy of Mind (same as PHIL 286)
      • PHIL 187. Philosophy of Action (same as PHIL 287)
    4. Cognition and Neuroscience.
      1. Introductory Cognition and Neuroscience.  One of the following:
        • PSYCH 45. Introduction to Learning and Memory
        • PSYCH 50. Introduction to Cognitive Neuroscience
      2. An additional undergraduate course in cognition and/or neurosciences (one of the following):
        • BIO 20. Introduction to Brain and Behavior (same as HUMBIO 21)
        • BIO 150. Human Behavioral Biology
        • HUMBIO 3B. Behavior, Health, and Development
        • OSPSANTG 48. Language and Thought
        • PSYCH 30. Introduction to Perception
        • PSYCH 45. Introduction to Learning and Memory (if not counted for 10a)
        • PSYCH 50. Introduction to Cognitive Neuroscience (if not counted for 10a)
        • PSYCH 60. Introduction to Developmental Psychology
        • PSYCH 60B. Introduction to Developmental Psychology
        • PSYCH 70. Introduction to Social Psychology
        • PSYCH 80. Introduction to Personality and Affective Science
        • PSYCH 120. Cellular Neuroscience: Cell Signaling and Behavior (same as BIO 153)
        • PSYCH 131. Language and Thought (same as PSYCH 262)
        • PSYCH 140. Introduction to Psycholinguistics (same as LINGUIST 145)
        • PSYCH 141. Cognitive Development
        • PSYCH 154. Judgment and Decision-Making
    5. Natural Language.
      1. Language and Mind: (one of the following):
        • LINGUIST 1. Introduction to Linguistics
        • LINGUIST 106. Introduction to Speech Perception
        • LINGUIST 140. Language Acquisition I (same as LINGUIST 240)
        • OSPSANTG 48. Language and Thought
        • PSYCH 131. Language and Thought (same as PSYCH 262)
        • PSYCH 140. Introduction to Psycholinguistics (same as LINGUIST 145)
      2. Linguistic Theory: (one of the following):
        • LINGUIST 105. Phonetics (same as LINGUIST 205A)
        • LINGUIST 110. Introduction to Phonology
        • LINGUIST 120. Introduction to Syntax
        • LINGUIST 121A. The Syntax of English
        • LINGUIST 121B. Crosslinguistic Syntax
        • LINGUIST 130A. Introduction to Semantics and Pragmatics (same as LINGUIST 230A)
        • LINGUIST 130B. Introduction to Lexical Semantics
        • LINGUIST 281. Computational Models of Linguistic Formalism [if taken for 3 or more units]
        • SYMSYS 184. Syntactic Theory and Implemetation (same as LINGUIST 184)
    6. Computation and Cognition. A course applying core technical skills  to cognition (one of the following):
      • CS 221. Artificial Intelligence: Principles and Techniques
      • CS 228. Probabilistic Graphical Models: Principles and Techniques
      • CS 229. Machine Learning
      • CS 231A. Computer Vision: From 3-D Reconstruction to Recognition
      • LINGUIST 180. From Languages to Information (same as CS 124, LINGUIST 280)
      • LINGUIST 182. Computational Theories of Syntax (same as LINGUIST 282)
      • NENS 220. Computational Neuroscience
      • PHIL 356C. Logic and Artificial Intelligence (same as CS 257)
      • PSYCH 109. An Introduction to Computation and Cognition
      • PSYCH 204. Computation and Cognition: the Probabilistic Approach
      • PSYCH 209. Neural Network and Deep Learning Models for Cognition and Cognitive Neuroscience
    7. Advanced Small Seminar Requirement. An upper division, limited-enrollment seminar drawing on material from other courses in the core.  Courses listed under Symbolic Systems Program offerings with numbers between Symsys 200 through 209 are acceptable, as are other courses which are announced in September of each academic year prior to the first day of classes. Beginning with courses taken in the 2013-2014 Academic Year, total enrollment must not exceed 20 students for a course to be approved as fulfilling the Advanced Small Seminar Requirement. A course taken to fulfill this requirement can also be counted toward another requirement, as part of either the core or a student’s concentration, but not both. Lists of approved seminars are linked below by year:

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