Areas of Application
The area of application is an integral part of the concentration. Students are encouraged to select an area of application that corresponds to an area of intellectual interest. Current concentrators have chosen application areas ranging from government, psychology, astronomy or astrophysics, and chemistry, to theoretical neuroscience.
Note: your transcript and diploma will not explicitly state your area of application.
Combining applied mathematics with astronomy or another similar physical science allows delving deeper into mathematical foundations, while maintaining a strong overview of the major concepts and methods.
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The biological sciences application area combines the foundation of a life sciences concentration with a focus on biological data analysis and/or modeling using computation, statistics, and mathematics.
At least one course should be a broad ("gateway", "portal", or "foundation") intermediatelevel course in a life sciences concentration:
 MCB 60, 63, 64, 65, 68 for molecular and cellular biology or for chemical and physical biology;
 OEB 5059 for integrative biology;
 MCB 80, 81,105,115,125 for neuroscience;
 SCRB 10 for human developmental & regenerative biology;
 HEB 1280, 1328, 1330, 1420 for human evolutionary biology.
At least three of the five application area courses should be "quantitative", meaning that they have substantial mathematical or computational content. The quantitative application area courses can be drawn from any area relevant to quantitative biology, not just life sciences courses but also including computer science, statistics, and applied math courses, provided they form a coherent plan. Some examples of life sciences courses that currently count as quantitative include:
LS50 Integrated science
MCB105 Systems neuroscience
MCB111 Mathematics in biology
MCB112 Biological data analysis
MCB131 Computational neuroscience
MCB195 Foundations of systems biology
MCB198 Advanced mathematical techniques for modern biology
MCB199 Statistical thermodynamics and quantitative biology
Neuro140 Biological and artificial intelligence
Neuro141 Physics of sensory systems in biology
Neuro1401 Computational cognitive neuroscience
OEB242 Population genetics
OEB252 Coalescent theory
Some examples of other courses suitable as quantitative AM/bio
application area courses include:
CS181 Machine learning
CS182 Artificial intelligence
Math153 Evolutionary dynamics
Stat 111 Introduction to statistical inference
Stat115 Computational biology and bioinformatics
Stat117 Data analysis in modern biostatistics
Stat 139 Linear models
AM 120 Applied linear algebra and big data
AM 121 Introduction to optimization: models and methods
ES 201 Decision theory
Notes:
Introductorylevel life sciences courses including LS1a/b and OEB10 do not count toward AM/bio concentration requirements, although they may be prerequisites for other courses.
The special fullyear freshman course LS50 Integrated Science can be counted as two courses: once in the application area (where it counts both as an intermediatelevel foundational course and as quantitative), and also toward the modeling category in the breadth requirement.
Theoretical chemistry provides an opportunity for several potential areas of application, in physical, inorganic, and organic chemistry.
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Applied Mathematics concentrators specializing in computer science will build a broader base of applicable mathematics and focus on those aspects of the subject which depend most directly on such mathematics.
For an application in computer science, students will take at least one course in the 120 series, as well as at least two more courses drawn from the 120s, 130s, 150s, 161, 175, or the 180s.
Note: CS 51 is recommended preparation for CS 136, CS 181, CS 182, so students with one of those courses on their plan of study who have not yet completed CS 51 will be required to have CS 51 on the plan as well. (CS 51 can be removed from the plan of study once it has been completed).
Applied Mathematics concentrators specializing in data science will take AM 120, Stat 111, CS 181 or CS 182 (as well as any courses that are recommended preparation for those), and two electives.
Recommended electives include MCB 112, Astro 100 and 193, additional statistics coursework beyond Stat 110/111, ES 201 and 202, further CS coursework, and econometrics.
The Decision and Control area is concerned with topics that are sometimes called operations research and/or systems engineering. The common theme is optimization, in various forms and contexts, both to understand natural systems and to design man made systems.
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AM students planning to pursue an application to the earth sciences should take the Physical Sciences 12 or Physics 15 sequence as important background knowledge. Courses in EPS that have both physics and 21a/21b prerequisites are appropriate for the application.
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Mathematical modeling is used extensively in economics, and it is generally agreed that the foundation of economic theory is formed on a mathematical basis. The requirements for applied mathematics and economics are made and continuously updated in cooperation with the Economics Department.
The birth of internet technology has strengthened the argument for combining computer science and economics into a single track. The core part of such a program should include Ec 1011a; one of CS 136, CS 134, 1052; and one of CS 181, CS 182, CS 183, MIT 6.036. Ec 1011a is forming the core of the economics and CS 181/182/MIT 6.036 is forming the core of the computer science in the plan. As for every application area, the overall program of five courses should form a coherent set of five courses.
Note: CS 51 is recommended preparation for CS 136, CS 181, CS 182, so students with one of those courses on their plan of study who have not yet completed CS 51 will be required to have CS 51 on the plan as well. (CS 51 can be removed from the plan of study once it has been completed).
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Three important general paths of study involve circuit design, signal processing/communications, and the mathematics of intelligent machines.
Applied Math concentrators on a Government Track are required to take at least 2 substantive (i.e., primarily about politics) Government classes and 3 Government courses that are more mathematically oriented.
Substantive courses (two Gov courses): Gov foundational courses (10, 20, 30, 40), Gov 97 Sophomore Tutorial (recommended), and other courses with Gov course numbers that focus on politics.
Note: Gov 50, 61, 62, 1005 do not count for the application area.
Core statistics course (one course): Gov 2000 Introduction to quantitative methods (recommended) or one of Stat 111 or 139 (accepted). The Gov 2000 courses are open to AM/Gov students
Core formal theory course (one course): Gov 2005 Formal Theory 1 (recommended) or one of Gov 1729 Models of Conflict in International Relations, 1780 International Political Economy, 94HL Political Economy of Development
One additional mathematical course: Gov 2001 Advanced quantitative research methodology, Gov 2002 Causal Inference, Gov 2003 Advanced Topics in Political Methodology, Gov 1430 Data Science to Save the World (this course can be added to a plan of study only after completion of the course, and only by petition based on the mathematical content of the course project), Gov 2006 Formal Theory 2, Gov 1006 Models.
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There are two main options in this area: macroscopic (or classical) physics and microscopic (or quantum) physics. While no specific course sequences are outlined here, programs involving astrophysics, biophysics, and the like are also possible.
Astrophysics
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Applied Mathematics concentrators specializing in psychology will build a psychology foundation while developing an understanding of complementary mathematics.
For an application in psychology, students will take one foundational psychology course, one advanced psychology course from within the Psychology Department, and three quantitative courses. One of the three quantitative courses must be a statistical inference course (Stat 111, Stat 139, Psych 1952, Econ 1126, Gov 2000). The other two can be drawn from Statistics, Computer Science, Economics, Engineering Sciences, or Mathematical Biology. Psych 1401 also counts as a quantitative course for the psychology application area. As with all applications, the five courses should form a coherent plan.
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This area is concerned with the design, implementation and study of algorithms for the approximate solution of continuous mathematical problems on digital computers: problems posed in the language of calculus and linear algebra, including differential and integral equations, root finding, and optimization.
Applied Math concentrators on a Sociology Track are expected to take at least 2 substantive classes in Sociology and 3 courses that are methodologically oriented. Two of the three methodological courses should be in sociology
Substantive courses: two courses drawn from foundational sociology courses (Soc 10001089) or from the tutorial in social theory (Soc 97)
Core statistics course (one course): Soc 2202 Intermediate quantitative research methods, Soc 2203 Advanced quantitative research methods, Stat 111 Introduction to statistical inference, or Stat 139 Linear models.
Two advanced methodological courses: Soc 90 Quantitative research labs, Soc 2203 Advanced quantitive research methods, Soc 2211 Analysis of longitudinal data, Soc 2272 Computational sociology, other Soc 22xx quantitative methods courses, Stat 140 Design of experiments, Stat 160 Design and analysis of sample surveys, Gov 2002 Causal inference, Gov 2003 Advanced topics in political methodology
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Applied Mathematics concentrators specializing in the Study of the Human Past will learn how to apply quantitative methods to historical datasets drawn from archaeological, genetic, historical, linguistic/philological, or textual sources. Students should expect to take 2 foundational courses and at least 1 quantitive course concerned with the human past in one or more of the participating departments (including Anthropology, East Asian Languages and Civilizations, Government, History, English) along with additional quantitatively oriented courses. For more information, contact amadvising@seas.harvard.edu