Institute for Data, Systems and Society
IAP/Spring
2025
IDS.012[J] Statistics, Computation and Applications
 ( )
(Same subject as 6.3730[J])
(Subject meets with 6.3732[J], IDS.131[J])
Prereq: (6.100B, (18.03, 18.06, or 18.C06), and (6.3700, 6.3800, 14.30, 16.09, or 18.05)) or permission of instructor
Units: 3-1-8
Lecture: MW11-12.30 (2-190) Recitation: W4 (36-144) or F10 (36-144) or F11 (36-156)
Hands-on analysis of data demonstrates the interplay between statistics and computation. Includes four modules, each centered on a specific data set, and introduced by a domain expert. Provides instruction in specific, relevant analysis methods and corresponding algorithmic aspects. Potential modules may include medical data, gene regulation, social networks, finance data (time series), traffic, transportation, weather forecasting, policy, or industrial web applications. Projects address a large-scale data analysis question. Students taking graduate version complete additional assignments. Enrollment limited; priority to Statistics and Data Science minors, and to juniors and seniors.
C. Uhler, N. Azizan, M. Roozbehani
No required or recommended textbooks
IDS.013[J] Statistical Thinking and Data Analysis
 () 
(Same subject as 15.075[J])
Prereq: 6.3700 or 15.069
Units: 3-1-8
Introduces a rigorous treatment of statistical data analysis while helping students develop a strong intuition for the strengths and limitations of various methods. Topics include statistical sampling and uncertainty, estimation, hypothesis testing, linear regression, classification, analysis of variation, and elements of data mining. Involves empirical use of hypothesis testing and other statistical methodologies in several domains, including the assessment of A-B experiments on the web and the identification of genes correlated with diseases.
Staff
IDS.014[J] Fundamentals of Statistics
( , )
(Same subject as 18.650[J])
(Subject meets with 18.6501)
Prereq: 6.3700 or 18.600
Units: 4-0-8
Lecture: MWF1 (2-190) Recitation: R10 (4-270) or R3 (4-153) or R4 (4-153) +final
A rapid introduction to the theoretical foundations of statistical methods that are useful in many applications. Covers a broad range of topics in a short amount of time with the goal of providing a rigorous and cohesive understanding of the modern statistical landscape. Mathematical language is used for intuition and basic derivations but not proofs. Main topics include: parametric estimation, confidence intervals, hypothesis testing, Bayesian inference, and linear and logistic regression. Additional topics may include: causal inference, nonparametric estimation, and classification.
Fall: P. Rigollet
Spring: A. Katsevich
Textbooks (Spring 2025)
IDS.045[J] System Safety
() 
(Same subject as 16.63[J])
Prereq: None
Units: 3-0-9
Introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems.
N. Leveson
IDS.050[J] Cybersecurity
() 
(Same subject as 17.447[J], MAS.460[J])
(Subject meets with 17.448[J], IDS.350[J], MAS.660[J])
Prereq: None
Units: 3-0-9
Lecture: T1-3 (E60-112) Recitation: T3 (E51-390) or R1 (1-136)
Focuses on the complexity of cybersecurity in a changing world. Examines national and international aspects of overall cyber ecology. Explores sources and consequences of cyber threats and different types of damages. Considers impacts for and of various aspects of cybersecurity in diverse geostrategic, political, business and economic contexts. Addresses national and international policy responses as well as formal and informal strategies and mechanisms for responding to cyber insecurity and enhancing conditions of cybersecurity. Students taking graduate version expected to pursue subject in greater depth through reading and individual research.
N. Choucri, S. Madnick, A. Pentland
No textbook information available
IDS.055[J] Science, Technology, and Public Policy
() 
(Same subject as 17.309[J], STS.082[J])
Prereq: None
Units: 4-0-8
Credit cannot also be received for 17.310, IDS.412, STS.482
Analysis of issues at the intersection of science, technology, public policy, and business. Cases drawn from antitrust and intellectual property rights; health and environmental policy; defense procurement and strategy; strategic trade and industrial policy; and R&D funding. Structured around theories of political economy, modified to take into account integration of uncertain technical information into public and private decision-making. Meets with 17.310 when offered concurrently.
Staff
IDS.057[J] Data and Society
() 
(Same subject as 11.155[J], STS.005[J])
Prereq: None
Units: 3-0-9
Introduces students to the social, political, and ethical aspects of data science work. Designed to create reflective practitioners who are able to think critically about how collecting, aggregating, and analyzing data are social processes and processes that affect people.
E. Medina, S. Williams
IDS.060[J] Environmental Law, Policy, and Economics: Pollution Prevention and Control
()
(Same subject as 1.801[J], 11.021[J], 17.393[J])
(Subject meets with 1.811[J], 11.630[J], 15.663[J], IDS.540[J])
Prereq: None
Units: 3-0-9
Lecture: TR3.30-5 (E51-057) +final
Analyzes federal and state regulation of air and water pollution, hazardous waste, greenhouse gas emissions, and production/use of toxic chemicals. Analyzes pollution/climate change as economic problems and failure of markets. Explores the role of science and economics in legal decisions. Emphasizes use of legal mechanisms and alternative approaches (i.e., economic incentives, voluntary approaches) to control pollution and encourage chemical accident and pollution prevention. Focuses on major federal legislation, underlying administrative system, and common law in analyzing environmental policy, economic consequences, and role of the courts. Discusses classical pollutants and toxic industrial chemicals, greenhouse gas emissions, community right-to-know, and environmental justice. Develops basic legal skills: how to read/understand cases, regulations, and statutes. Students taking graduate version explore the subject in greater depth.
N. Ashford, C. Caldart
Textbooks (Spring 2025)
IDS.061[J] Regulation of Chemicals, Radiation, and Biotechnology
()
Not offered regularly; consult department
(Same subject as 1.802[J], 11.022[J])
(Subject meets with 1.812[J], 10.805[J], 11.631[J], IDS.436[J], IDS.541[J])
Prereq: IDS.060 or permission of instructor
Units: 3-0-9
Focuses on policy design and evaluation in the regulation of hazardous substances and processes. Includes risk assessment, industrial chemicals, pesticides, food contaminants, pharmaceuticals, radiation and radioactive wastes, product safety, workplace hazards, indoor air pollution, biotechnology, victims' compensation, and administrative law. Health and economic consequences of regulation, as well as its potential to spur technological change, are discussed for each regulatory regime. Students taking the graduate version are expected to explore the subject in greater depth.
Staff
IDS.062[J] Global Environmental Negotiations
()
Not offered regularly; consult department
(Same subject as 12.346[J])
Prereq: Permission of instructor
Units: 2-0-4
Practical introduction to global environmental negotiations designed for science and engineering students. Covers basic issues in international negotiations, such as North-South conflict, implementation and compliance, trade, and historical perspective on global environmental treaties. Offers hands-on practice in developing and interpreting international agreements through role-play simulations and observation of ongoing climate change negotiating processes. Students taking graduate version complete additional assignments.
N. E. Selin
IDS.063[J] People and the Planet: Environmental Governance and Science
()
(Same subject as 12.387[J], 15.874[J])
Prereq: None
Units: 3-0-6
Introduces governance and science aspects of complex environmental problems and approaches to solutions. Introduces quantitative analyses and methodological tools to analyze environmental issues that have human and natural components. Demonstrates concepts through a series of in-depth case studies of environmental governance and science problems. Students develop writing, quantitative modeling, and analytical skills in assessing environmental systems problems and developing solutions. Through experiential activities, such as modeling and policy exercises, students engage with the challenges and possibilities of governance in complex, interacting systems, including biogeophysical processes and societal and stakeholder interactions.
A. Siddiqi
IDS.065[J] Energy Systems for Climate Change Mitigation
()
(Same subject as 1.067[J], 10.421[J])
(Subject meets with 1.670[J], 10.621[J], IDS.521[J])
Prereq: (Calculus I (GIR), Chemistry (GIR), and Physics I (GIR)) or permission of instructor
Units: 3-0-9
Reviews the contributions of energy systems to global greenhouse gas emissions, and the levers for reducing those emissions. Lectures and projects focus on evaluating energy systems against climate policy goals, using performance metrics such as cost, carbon intensity, and others. Student projects explore pathways for realizing emissions reduction scenarios. Projects address the climate change mitigation potential of energy technologies (hardware and software), technological and behavioral change trajectories, and technology and policy portfolios. Background in energy systems strongly recommended. Students taking the graduate version complete additional assignments and explore the subject in greater depth. Preference to students in the Energy Studies or Environment and Sustainability minors.
J. Trancik
IDS.066[J] Law, Technology, and Public Policy
()
(Same subject as 11.122[J])
(Subject meets with 11.422[J], 15.655[J], IDS.435[J])
Prereq: None
Units: 3-0-9
Examines how law, economics, and technological change shape public policy, and how law can sway technological change; how the legal system responds to environmental, safety, energy, social, and ethical problems; how law and markets interact to influence technological development; and how law can affect wealth distribution, employment, and social justice. Covers energy/climate change; genetic engineering; telecommunications and role of misinformation; industrial automation; effect of regulation on technological innovation; impacts of antitrust law on innovation and equity; pharmaceuticals; nanotechnology; cost/benefit analysis as a decision tool; public participation in governmental decisions affecting science and technology; corporate influence on technology and welfare; and law and economics as competing paradigms to encourage sustainability. Students taking graduate version explore subject in greater depth.
N. Ashford
IDS.075[J] Transportation: Foundations and Methods
()
(Same subject as 1.041[J])
(Subject meets with 1.200[J], 11.544[J], IDS.675[J])
Prereq: (1.010A and (1.00 or 1.000)) or permission of instructor
Units: 3-1-8
 Subject Cancelled
Covers core analytical and numerical methods for modeling, planning, operations, and control of transportation systems. Traffic flow theory, vehicle dynamics and behavior, numerical integration and simulation, graphical analysis. Properties of delays, queueing theory. Resource allocation, optimization models, linear and integer programming. Autonomy in transport, Markov Decision Processes, reinforcement learning, deep learning. Applications drawn broadly from land, air, and sea transport; private and public sector; transport of passengers and goods; futuristic, modern, and historical. Hands-on computational labs. Linear algebra background is encouraged but not required. Students taking graduate version complete additional assignments.
C. Wu
IDS.131[J] Statistics, Computation and Applications
 ()
(Same subject as 6.3732[J])
(Subject meets with 6.3730[J], IDS.012[J])
Prereq: (6.100B, (18.03, 18.06, or 18.C06), and (6.3700, 6.3800, 14.30, 16.09, or 18.05)) or permission of instructor
Units: 3-1-8
Lecture: MW11-12.30 (2-190) Recitation: W4 (36-144) or F10 (36-144) or F11 (36-156)
Hands-on analysis of data demonstrates the interplay between statistics and computation. Includes four modules, each centered on a specific data set, and introduced by a domain expert. Provides instruction in specific, relevant analysis methods and corresponding algorithmic aspects. Potential modules may include medical data, gene regulation, social networks, finance data (time series), traffic, transportation, weather forecasting, policy, or industrial web applications. Projects address a large-scale data analysis question. Students taking graduate version complete additional assignments. Limited enrollment; priority to Statistics and Data Science minors and to juniors and seniors.
C. Uhler, N. Azizan, M. Roozbehani
No required or recommended textbooks
IDS.136[J] Graphical Models: A Geometric, Algebraic, and Combinatorial Perspective
()
Not offered regularly; consult department
(Same subject as 6.7820[J])
Prereq: 6.3702 and 18.06
Units: 3-0-9
Provides instruction in the geometric, algebraic and combinatorial perspective on graphical models. Presents methods for learning the underlying graph and inferring its parameters. Topics include exponential families, duality theory, conic duality, polyhedral geometry, undirected graphical models, Bayesian networks, Markov properties, total positivity of distributions, hidden variables, and tensor decompositions.
C. Uhler
IDS.140[J] Reinforcement Learning: Foundations and Methods
()
(Same subject as 1.127[J], 6.7920[J])
Prereq: 6.3700 or permission of instructor
Units: 4-0-8
Examines reinforcement learning (RL) as a methodology for approximately solving sequential decision-making under uncertainty, with foundations in optimal control and machine learning. Provides a mathematical introduction to RL, including dynamic programming, statistical, and empirical perspectives, and special topics. Core topics include: dynamic programming, special structures, finite and infinite horizon Markov Decision Processes, value and policy iteration, Monte Carlo methods, temporal differences, Q-learning, stochastic approximation, and bandits. Also covers approximate dynamic programming, including value-based methods and policy space methods. Applications and examples drawn from diverse domains. Focus is mathematical, but is supplemented with computational exercises. An analysis prerequisite is suggested but not required; mathematical maturity is necessary.
C. Wu
IDS.145[J] Data Mining: Finding the Models and Predictions that Create Value
(); second half of term
(Same subject as 15.062[J])
(Subject meets with 15.0621)
Prereq: 15.060, 15.075, or permission of instructor
Units: 2-0-4
Begins Mar 31. Lecture: MW4-5.30 (E51-315) Recitation: T4 (E62-262)
Introduction to data mining, data science, and machine learning for recognizing patterns, developing models and predictive analytics, and making intelligent use of massive amounts of data collected via the internet, e-commerce, electronic banking, medical databases, etc. Topics include logistic regression, association rules, tree-structured classification and regression, cluster analysis, discriminant analysis, and neural network methods. Presents examples of successful applications in credit ratings, fraud detection, marketing, customer relationship management, investments, and synthetic clinical trials. Introduces data-mining software (R and Python). Grading based on homework, cases, and a term project. Expectations and evaluation criteria differ for students taking the undergraduate version; consult syllabus or instructor for specific details.
R. Welsch
Textbooks (Spring 2025)
IDS.147[J] Statistical Machine Learning and Data Science
()
Not offered regularly; consult department
(Same subject as 15.077[J])
Prereq: Permission of instructor
Units: 4-0-8
Advanced introduction to theory and application of statistics, data-mining and machine learning using techniques from management science, marketing, finance, consulting, and bioinformatics. Covers bootstrap theory of estimation, testing, nonparametric statistics, analysis of variance, experimental design, categorical data analysis, regression analysis, MCMC, and Bayesian methods. Focuses on data mining, supervised learning, and multivariate analysis. Topics chosen from logistic regression, principal components and dimension reduction; discrimination and classification analysis, trees (CART), partial least squares, nearest neighbors, regularized methods, support vector machines, boosting and bagging, clustering, independent component analysis, and nonparametric regression. Uses statistics software R, Python, and MATLAB. Grading based on homework, cases, and a term project.
R. Welsch
IDS.160[J] Mathematical Statistics: a Non-Asymptotic Approach
()
(Same subject as 9.521[J], 18.656[J])
Prereq: (6.7700, 18.06, and 18.6501) or permission of instructor
Units: 3-0-9
Lecture: TR1-2.30 (46-3002)
Introduces students to modern non-asymptotic statistical analysis. Topics include high-dimensional models, nonparametric regression, covariance estimation, principal component analysis, oracle inequalities, prediction and margin analysis for classification. Develops a rigorous probabilistic toolkit, including tail bounds and a basic theory of empirical processes
S. Rakhlin, P. Rigollet
No required or recommended textbooks
IDS.190 Doctoral Seminar in Statistics and Data Science
()
Prereq: None
Units: 1-0-2 [P/D/F]
Interdisciplinary seminar explores diverse topics in statistics and data science. Restricted to students in the Interdisciplinary Doctoral Program in Statistics.
Staff
IDS.250[J] The Theory of Operations Management
() 
(Same subject as 1.271[J], 15.764[J])
Prereq: (6.7210 and 6.7700) or permission of instructor
Units: 3-0-9
Lecture: TR2.30-4 (E51-151)
Provides mathematical foundations underlying the theory of operations management. Covers both classic and state-of-the-art results in various application domains, including inventory management, supply chain management and logistics, behavioral operations, healthcare management, service industries, pricing and revenue management, and auctions. Studies a wide range of mathematical and analytical techniques, such as dynamic programming, stochastic orders, principal-agent models and contract design, behavioral and experimental economics, algorithms and approximations, data-driven and learning models, and mechanism design. Also provides practical experience in how to apply the theoretical models to solve OM problems in business settings. Specific topics vary from year to year.
D. Freund
No textbook information available
IDS.305[J] Business and Operations Analytics
(); first half of term
(Same subject as 1.275[J])
Prereq: Permission of instructor
Units: 2-0-4
Ends Mar 21. Lecture: T10-1 (66-168)
Provides instruction on identifying, evaluating, and capturing business analytics opportunities that create value. Also provides basic instruction in analytics methods and case study analysis of organizations that successfully deployed these techniques.
D. Simchi-Levi
No required or recommended textbooks
IDS.332 System Design and Management for a Changing World: Combined
()
Engineering School-Wide Elective Subject.
(Offered under: 1.146, 16.861, EM.422, IDS.332)
Prereq: Permission of instructor
Units: 3-0-9
Credit cannot also be received for EM.423, IDS.333
Practical-oriented subject that builds upon theory and methods and culminates in extended application. Covers methods to identify, value, and implement flexibility in design (real options). Topics include definition of uncertainties, simulation of performance for scenarios, screening models to identify desirable flexibility, decision analysis, and multidimensional economic evaluation. Students demonstrate proficiency through an extended application to a system design of their choice. Complements research or thesis projects. Class is "flipped" to maximize student engagement and learning. Meets with IDS.333 in the first half of term. Enrollment limited.
R. de Neufville
IDS.333[J] System Design and Management for a Changing World: Tools
(); first half of term
(Same subject as EM.423[J])
Prereq: None
Units: 3-0-3
Credit cannot also be received for 1.146, 16.861, EM.422, IDS.332
Focuses on design choices and decisions under uncertainty. Topics include identification and description of uncertainties using probability distributions; the calculation of commensurate measures of value, such as expected net present values; Monte Carlo simulation and risk analysis; and the use of decision analysis to explore alternative strategies and identify optimal initial choices. Presents applied analysis of practical examples from a variety of engineering systems using spreadsheet and decision analysis software. Class is "flipped" to maximize student engagement and learning. Meets with IDS.332 first half of term.
R. de Neufville
IDS.334[J] System Design and Management for a Changing World: Projects
(IDS.330)
(, )
(Same subject as EM.424[J])
Prereq: IDS.333 or permission of instructor
Units: 3-0-3
Ends Mar 21. Lecture: TR10.30-12 (1-390)
Focuses on implementation of flexibility (real options) in the design of products, start-ups, ongoing management of operations, or policy plans. Applies the methods presented in IDS.333: recognition of uncertainty, identification of best opportunities for flexibility, and valuation of these options and their effective implementation. Students work on their own project concept, for which they develop a dynamic business plan for design, deployment, and most beneficial implementation of their system over time. Useful complement to thesis or research projects. Class is "flipped" to maximize student engagement and learning. Subject meets in second half of term in the fall and first half of term in the spring.
Fall: R. de Neufville
Spring: R. de Neufville
Textbooks (Spring 2025)
IDS.336[J] Systems Architecting Applied to Enterprises
()
(Same subject as 16.855[J], EM.429[J])
Prereq: Permission of instructor
Units: 3-0-9
Lecture: T EVE (4-7 PM) (1-390)
Focuses on understanding, designing and transforming sociotechnical enterprises using systems principles and practices. Includes discussions and reading on enterprise theory, systems architecting, transformation challenges and case studies of evolving enterprises. Covers frameworks and methods for ecosystem analysis, stakeholder analysis, design thinking, systems architecture and evaluation, and human-centered enterprise design strategies. Students engage in interactive breakout sessions during class and participate in a selected small team project to design a future architecture for a real-world enterprise. Selected projects are based on student interests in enterprises such as small, medium, or large companies, government agencies, academic units, start-ups, and nonprofit organizations.
D. Rhodes
No required or recommended textbooks
IDS.337[J] Aerospace Biomedical and Life Support Engineering
()
(Same subject as 16.423[J], HST.515[J])
Prereq: 16.06, 16.400, or permission of instructor
Units: 3-0-9
Fundamentals of human performance, physiology, and life support impacting engineering design and aerospace systems. Topics include effects of gravity on the muscle, skeletal, cardiovascular, and neurovestibular systems; human/pilot modeling and human/machine design; flight experiment design; and life support engineering for extravehicular activity (EVA). Case studies of current research are presented. Assignments include a design project, quantitative homework sets, and quizzes emphasizing engineering and systems aspects.
L. Petersen
IDS.338[J] Multidisciplinary Design Optimization
()
(Same subject as 16.888[J], EM.428[J])
Prereq: 18.085 or permission of instructor
Units: 3-1-8
Systems modeling for design and optimization. Selection of design variables, objective functions and constraints. Overview of principles, methods and tools in multidisciplinary design optimization (MDO). Subsystem identification, development and interface design. Design of experiments (DOE). Review of linear (LP) and non-linear (NLP) constrained optimization formulations. Scalar versus vector optimization problems. Karush-Kuhn-Tucker (KKT) conditions of optimality, Lagrange multipliers, adjoints, gradient search methods, sensitivity analysis, geometric programming, simulated annealing, genetic algorithms and particle swarm optimization. Constraint satisfaction problems and isoperformance. Non-dominance and Pareto frontiers. Surrogate models and multifidelity optimization strategies. System design for value. Students execute a term project in small teams related to their area of interest.
O. de Weck
IDS.339[J] Space Systems Engineering
()
(Same subject as 16.89[J])
Prereq: 16.842, 16.851, or permission of instructor
Units: 4-2-6
Lecture: TR1.30-3 (33-218) Lab: TBA
Focus on developing space system architectures. Applies subsystem knowledge gained in 16.851 to examine interactions between subsystems in the context of a space system design. Principles and processes of systems engineering including developing space architectures, developing and writing requirements, and concepts of risk are explored and applied to the project. Subject develops, documents, and presents a conceptual design of a space system including a preliminary spacecraft design.
G. Lordos, E.F. Crawley
No textbook information available
IDS.340[J] System Safety Concepts
()
(Same subject as 16.863[J])
Prereq: Permission of instructor
Units: 3-0-9
Covers important concepts and techniques in designing and operating safety-critical systems. Topics include the nature of risk, formal accident and human error models, causes of accidents, fundamental concepts of system safety engineering, system and software hazard analysis, designing for safety, fault tolerance, safety issues in the design of human-machine interaction, verification of safety, creating a safety culture, and management of safety-critical projects. Includes a class project involving the high-level system design and analysis of a safety-critical system. Enrollment may be limited.
N. Leveson
IDS.341[J] Concepts in the Engineering of Software
()
(Same subject as 16.355[J])
Prereq: Permission of instructor
Units: 3-0-9
Lecture: F9-12 (33-422)
Reading and discussion on issues in the engineering of software systems and software development project design. Includes the present state of software engineering, what has been tried in the past, what worked, what did not, and why. Topics may differ in each offering, but are chosen from the software process and life cycle; requirements and specifications; design principles; testing, formal analysis, and reviews; quality management and assessment; product and process metrics; COTS and reuse; evolution and maintenance; team organization and people management; and software engineering aspects of programming languages. Enrollment may be limited.
N. G. Leveson
No required or recommended textbooks
IDS.350[J] Cybersecurity
()
(Same subject as 17.448[J], MAS.660[J])
(Subject meets with 17.447[J], IDS.050[J], MAS.460[J])
Prereq: Permission of instructor
Units: 3-0-9
Lecture: T1-3 (E60-112)
Focuses on the complexity of cybersecurity in a changing world. Examines national and international aspects of overall cyber ecology. Explores sources and consequences of cyber threats and different types of damages. Considers impacts for and of various aspects of cybersecurity in diverse geostrategic, political, business and economic contexts. Addresses national and international policy responses as well as formal and informal strategies and mechanisms for responding to cyber insecurity and enhancing conditions of cybersecurity. Students taking graduate version expected to pursue subject in greater depth through reading and individual research.
N. Choucri, S. Madnick, A. Pentland
No textbook information available
IDS.405 Critical Internet Studies
(CMS.867)
()
(Subject meets with 21W.791[J], CMS.614[J], WGS.280[J])
Prereq: None
Units: 3-0-9
Lecture: W2-5 (56-169)
Focuses on the power dynamics in internet-related technologies (including social networking platforms, surveillance technology, entertainment technologies, and emerging media forms). Theories and readings focus on the cultural, social, economic, and political aspects of internet use and design, with a special attention to gender and race. Topics include: online communication and communities, algorithms and search engines, activism and online resistance, surveillance and privacy, content moderation and platform governance, and the spread of dis- and misinformation. Instruction and practice in written and oral communication provided. Students taking the graduate version complete additional readings and assignments.
T.L. Taylor
No required or recommended textbooks
IDS.410 Modeling and Assessment for Policy
()
Prereq: None
Units: 3-0-6
Explores how scientific information and quantitative models can be used to inform policy decision-making. Develops an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. Addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models.
N. E. Selin
IDS.411 Concepts and Research in Technology and Policy
()
Prereq: Permission of instructor
Units: 3-0-6
Lecture: TR11-12.30 (56-114)
Core integrative subject, with substantive participation from a series of guest faculty lecturers, examines key technology-policy concepts. Explores alternative framings of roles of technology in policy, emphasizing the implications of these alternatives upon problem-solving in the area. Exercises prepare students to apply these concepts in the framing of their thesis research. Preference to first-year students in the Technology and Policy Program.
F. Field
Textbooks (Spring 2025)
IDS.412[J] Science, Technology, and Public Policy
()
(Same subject as 17.310[J], STS.482[J])
Prereq: Permission of instructor
Units: 4-0-8
Credit cannot also be received for 17.309, IDS.055, STS.082
Analysis of issues at the intersection of science, technology, public policy, and business. Cases drawn from antitrust and intellectual property rights; health and environmental policy; defense procurement and strategy; strategic trade and industrial policy; and R&D funding. Structured around theories of political economy, modified to take account of integration of uncertain technical information into public and private decision-making. Meets with 17.309 when offered concurrently.
N. Selin
IDS.435[J] Law, Technology, and Public Policy
()
(Same subject as 11.422[J], 15.655[J])
(Subject meets with 11.122[J], IDS.066[J])
Prereq: None
Units: 3-0-9
Examines how law, economics, and technological change shape public policy, and how law can sway technological change; how the legal system responds to environmental, safety, energy, social, and ethical problems; how law and markets interact to influence technological development; and how law can affect wealth distribution, employment, and social justice. Covers energy/climate change; genetic engineering; telecommunications and the role of misinformation; industrial automation; effect of regulation on technological innovation; impacts of antitrust law on innovation and equity; pharmaceuticals; nanotechnology; cost/benefit analysis as a decision tool; public participation in governmental decisions affecting science and technology; corporate influence on technology and welfare; and law and economics as competing paradigms to encourage sustainability. Students taking graduate version explore subject in greater depth.
N. Ashford, C. Caldart
IDS.436[J] Technology, Law, and the Working Environment
()
Not offered regularly; consult department
(Same subject as 10.805[J])
(Subject meets with 1.802[J], 1.812[J], 11.022[J], 11.631[J], IDS.061[J], IDS.541[J])
Prereq: Permission of instructor
Units: 3-0-6
Addresses relationship between technology-related problems and the law applicable to work environment. National Labor Relations Act, Occupational Safety and Health Act. Toxic Substances Control Act, state worker's compensation, and suits by workers in the courts discussed. Problems related to occupational health and safety, collective bargaining as a mechanism for altering technology in the workplace, job alienation, productivity, and the organization of work addressed. Prior courses or experience in the environmental, public health, or law-related areas.
Staff
IDS.437[J] Technology, Globalization, and Sustainable Development
()
(Same subject as 1.813[J], 11.466[J], 15.657[J])
Prereq: Permission of instructor
Units: 3-0-9
Investigates sustainable development, taking a broad view to include not only a healthy economic base, but also a sound environment, stable and rewarding employment, adequate purchasing power and earning capacity, distributional equity, national self-reliance, and maintenance of cultural integrity. Explores national, multinational, and international political and legal mechanisms to further sustainable development through transformation of the industrial state. Addresses the importance of technological innovation and the financial crisis of 2008 and the emergence of the Covid-19 pandemic, Russia's invasion of Ukraine, and inflation, as well as governmental interventions to reduce inequality.
N. Ashford
IDS.448 Professional Development: Policy Hackathon
()
Prereq: None
Units: 2-0-4 [P/D/F]
Bridges knowledge to action for student organizers of the MIT Policy Hackathon. Students work with stakeholders to define needs for information and analysis, identify appropriate data sets, and craft problem statements that aim to provide actionable outputs for decision-making. Builds competence in management and organization, networking, presentation, and fundraising. Restricted to the student organizers for the MIT Policy Hackathon.
C. Ortiz
IDS.449 Technology Policy Internship and Professional Perspectives Seminar
(, )
Prereq: IDS.411 or permission of instructor
Units: 1-1-1 [P/D/F]
Lecture: F12-2 (E25-117)
Seminar examines what technology policy is in practice. Considers the question of "Who achieves what, when, how, and why?" regarding technology and policy. Students who completed summer internships present and dissect their experiences with special reference to specific cases in which they participated. Develops perspectives on practice in the field through sessions with alumni, other practitioners, and development professionals within MIT.
Fall: Staff
Spring: Staff
No required or recommended textbooks
IDS.521[J] Energy Systems for Climate Change Mitigation
()
(Same subject as 1.670[J], 10.621[J])
(Subject meets with 1.067[J], 10.421[J], IDS.065[J])
Prereq: Permission of instructor
Units: 3-0-9
Reviews the contributions of energy systems to global greenhouse gas emissions, and the levers for reducing those emissions. Lectures and projects focus on evaluating energy systems against climate policy goals, using performance metrics such as cost, carbon intensity, and others. Student projects explore pathways for realizing emissions reduction scenarios. Projects address the climate change mitigation potential of energy technologies (hardware and software), technological and behavioral change trajectories, and technology and policy portfolios. Background in energy systems strongly recommended. Students taking the graduate version complete additional assignments and explore the subject in greater depth.
J. Trancik
IDS.522 Mapping and Evaluating New Energy Technologies
()
Prereq: Permission of instructor
Units: 3-0-9
Project-based seminar reviews recent developments in energy conversion and storage technologies. Merits of alternative technologies are debated based on their environmental performance and cost, and their potential improvement and scalability. Project teams develop qualitative insights, quantitative models, and interactive visualization tools to inform the future development of technologies. Models may probe how the impact of a technology depends on assumptions about future advancements in performance, and how quantitative performance targets can be estimated to inform investment and design decisions. Other projects may develop models to inform rational investments in a portfolio of technologies based on economic and environmental performance and scalability constraints. Both information-based (e.g., software and codified practices) and physical technologies will be discussed.
J. Trancik
IDS.524[J] People and the Planet: Environmental Histories and Engineering
()
Not offered regularly; consult department
(Same subject as 11.204[J])
(Subject meets with 11.004[J], STS.033[J])
Prereq: None
Units: 3-3-6
Explores historical and cultural aspects of complex environmental problems and engineering approaches to sustainable solutions. Introduces quantitative analyses and methodological tools to understand environmental issues that have human and natural components. Demonstrates concepts through a series of historical and cultural analyses of environmental challenges and their engineering responses. Builds writing, quantitative modeling, and analytical skills in assessing environmental systems problems and developing engineering solutions. Through environmental data gathering and analysis, students engage with the challenges and possibilities of engineering in complex, interacting systems, and investigate plausible, symbiotic, systems-oriented solutions. Students taking graduate version complete additional analysis of reading assignments and a more in-depth and longer final paper.
Staff
IDS.526[J] Sustainability Science and Engineering
()
Not offered regularly; consult department
(Same subject as 12.845[J])
Prereq: None
Units: 3-0-6
Introduces and develops core ideas and concepts in the field of sustainability science and engineering from an engineering systems perspective. Takes an interdisciplinary approach to discuss case studies of sustainability systems research. Exposes students to techniques for sustainability research across engineering, natural and social science disciplines. Term projects focus on applying techniques.
Staff
IDS.540[J] Environmental Law, Policy, and Economics: Pollution Prevention and Control
()
(Same subject as 1.811[J], 11.630[J], 15.663[J])
(Subject meets with 1.801[J], 11.021[J], 17.393[J], IDS.060[J])
Prereq: None
Units: 3-0-9
Lecture: TR3.30-5 (E51-057) +final
Analyzes federal and state regulation of air and water pollution, hazardous waste, greenhouse gas emissions, and production/use of toxic chemicals. Analyzes pollution/climate change as economic problems and failure of markets. Explores the role of science and economics in legal decisions. Emphasizes use of legal mechanisms and alternative approaches (i.e., economic incentives, voluntary approaches) to control pollution and encourage chemical accident and pollution prevention. Focuses on major federal legislation, underlying administrative system, and common law in analyzing environmental policy, economic consequences, and role of the courts. Discusses classical pollutants and toxic industrial chemicals, greenhouse gas emissions, community right-to-know, and environmental justice. Develops basic legal skills: how to read/understand cases, regulations, and statutes. Students taking graduate version explore the subject in greater depth.
N. Ashford, C. Caldart
Textbooks (Spring 2025)
IDS.541[J] Regulation of Chemicals, Radiation, and Biotechnology
()
Not offered regularly; consult department
(Same subject as 1.812[J], 11.631[J])
(Subject meets with 1.802[J], 10.805[J], 11.022[J], IDS.061[J], IDS.436[J])
Prereq: IDS.540 or permission of instructor
Units: 3-0-9
Focuses on policy design and evaluation in the regulation of hazardous substances and processes. Includes risk assessment, industrial chemicals, pesticides, food contaminants, pharmaceuticals, radiation and radioactive wastes, product safety, workplace hazards, indoor air pollution, biotechnology, victims' compensation, and administrative law. Health and economic consequences of regulation, as well as its potential to spur technological change, are discussed for each regulator regime. Students taking the graduate version are expected to explore the subject in greater depth.
Staff
IDS.620[J] Principles and Practice of Drug Development
()
(Same subject as 10.547[J], 15.136[J], HST.920[J])
Prereq: Permission of instructor
Units: 3-0-6
Description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules. Economic and financial considerations of the drug development process. Multidisciplinary perspective from faculty in clinical; life; and management sciences; as well as industry guests.
S. Finkelstein
IDS.670[J] Planning and Design of Airport Systems
()
Not offered regularly; consult department
(Same subject as 1.231[J], 16.781[J])
Prereq: None
Units: 3-0-9
Focuses on current practice, developing trends, and advanced concepts in airport design and planning. Considers economic, environmental, and other trade-offs related to airport location, as well as the impacts of emphasizing "green" measures. Includes an analysis of the effect of airline operations on airports. Topics include demand prediction, determination of airfield capacity, and estimation of levels of congestion; terminal design; the role of airports in the aviation and transportation system; access problems; optimal configuration of air transport networks and implications for airport development; and economics, financing, and institutional aspects. Special attention to international practice and developments.
R. de Neufville, H. Balakrishnan, A.R. Odoni
IDS.675[J] Transportation: Foundations and Methods
()
(Same subject as 1.200[J], 11.544[J])
(Subject meets with 1.041[J], IDS.075[J])
Prereq: (1.010A and (1.00 or 1.000)) or permission of instructor
Units: 3-1-8
Subject Cancelled
Covers core analytical and numerical methods for modeling, planning, operations, and control of transportation systems. Traffic flow theory, vehicle dynamics and behavior, numerical integration and simulation, graphical analysis. Properties of delays, queueing theory. Resource allocation, optimization models, linear and integer programming. Autonomy in transport, Markov Decision Processes, reinforcement learning, deep learning. Applications drawn broadly from land, air, and sea transport; private and public sector; transport of passengers and goods; futuristic, modern, and historical. Hands-on computational labs. Linear algebra background is encouraged but not required. Students taking graduate version complete additional assignments.
C. Wu
IDS.700[J] Applied Probability and Stochastic Models
()
Not offered regularly; consult department
(Same subject as 1.203[J], 15.073[J])
Prereq: 6.3700 or 18.600
Units: 3-0-9
A vigorous use of probabilistic models to approximate real-life situations in Finance, Operations Management, Economics, and Operations Research. Emphasis on how to develop a suitable probabilistic model in a given setting and, merging probability with statistics, and on how to validate a proposed model against empirical evidence. Extensive treatment of Monte Carlo simulation for modeling random processes when analytic solutions are unattainable.
Staff
IDS.730[J] Logistics Systems
()
(Same subject as 1.260[J], 15.770[J], SCM.260[J])
(Subject meets with SCM.271)
Prereq: Permission of instructor
Units: 3-0-9
Provides an introduction to supply chain management from both analytical and practical perspectives. Taking a unified approach, students develop a framework for making intelligent decisions within the supply chain. Covers key logistics functions, such as demand planning, procurement, inventory theory and control, transportation planning and execution, reverse logistics, and flexible contracting. Explores concepts such as postponement, portfolio management, and dual sourcing. Emphasizes skills necessary to recognize and manage risk, analyze various tradeoffs, and model logistics systems. SCM.271 meets with SCM.260, but has fewer assignments.
Angela Acocella, Chris Caplice
IDS.735[J] Supply Chain Analytics
()
(Same subject as 1.273[J], 15.762[J])
Prereq: 15.761 or SCM.260
Units: 3-0-9
Focuses on effective supply chain strategies for companies that operate globally, with emphasis on how to plan and integrate supply chain components into a coordinated system. Students are exposed to concepts and models important in supply chain planning with emphasis on key tradeoffs and phenomena. Introduces and utilizes key tactics such as risk pooling and inventory placement, integrated planning and collaboration, and information sharing. Lectures, computer exercises, and case discussions introduce various models and methods for supply chain analysis and optimization.
Staff
IDS.736[J] Supply Chain: Capacity Analytics
(); second half of term
Not offered regularly; consult department
(Same subject as 1.274[J], 15.763[J])
Prereq: 15.761, 15.778, or SCM.260
Units: 2-0-4
Focuses on decision making for system design, as it arises in manufacturing systems and supply chains. Students exposed to frameworks and models for structuring the key issues and trade-offs. Presents and discusses new opportunities, issues and concepts introduced by the internet and e-commerce. Introduces various models, methods and software tools for logistics network design, capacity planning and flexibility, make-buy, and integration with product development. Industry applications and cases illustrate concepts and challenges. Recommended for Operations Management concentrators. Second half-term subject.
Staff
IDS.900 Doctoral Seminar in Social and Engineering Systems
()
Prereq: Permission of instructor
Units: 2-0-1 [P/D/F]
Introduces doctoral students to IDSS research areas. Preference to first-year students in SES.
Jadbabaie, A., Abadie, A.
IDS.910 Leadership Development
(); partial term
Not offered regularly; consult department
Prereq: Permission of instructor
Units: 1-1-1 [P/D/F]
Seminar environment created to develop leadership capabilities, and to take advantage of leadership opportunities. An initial Outward Bound experience builds trust, teamwork and communications. Readings and assignments emphasize the characteristics of desired leadership skills. Global leaders participate in the Leadership Lunch series to share their experiences and recommendations. Discussions explore leadership development. Culminates in a personal leadership plan. Restricted to entering students in the Technology and Policy program or instructor permission.
Staff
IDS.950 Independent Study in Data, Systems, and Society
(,  , ,  )
Prereq: Permission of IDSS Academic Office
Units arranged [P/D/F]
TBA.
For graduate students in IDSS. Individual study in data, systems, and society. Intended to expose student to expert-level domain material. Supervised by a member of MIT's teaching staff.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.951 Independent Study in Technology and Policy
(, , , )
Prereq: Permission of TPP Education Office
Units arranged [P/D/F]
TBA.
For graduate students in TPP. Individual study in technology and policy. Intended to expose student to expert-level domain material. Supervised by a member of MIT's teaching staff.
Fall: F. Field
IAP: F. Field
Spring: F. Field
Summer: F. Field
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.955 Practical Experience in Data, Systems, and Society
(, , , )
Prereq: None
Units arranged [P/D/F]
TBA.
For IDSS doctoral students participating in off-campus practical experiences in data, systems, and society. Before registering for this subject students must have a training offer from a company or organization, must identify a research advisor, and must receive prior approval from the IDSS Academic Office. Upon completion of the experience students must submit a letter from the company or organization describing the goals accomplished and a substantive final report to the MIT advisor.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.956 Practical Experience in Technology and Policy
(, , , )
Prereq: None
Units arranged [P/D/F]
TBA.
For TPP students participating in off-campus internship experiences in technology and policy. Before registering for this subject, students must have an employment offer from a company or organization, must identify a research advisor, and must receive prior approval from the TPP Education Office. Upon completion of the internship, student must submit a letter from the employer describing the work accomplished, along with a substantive final report from the student approved by the MIT advisor.
Fall: F. Field
IAP: F. Field
Spring: F. Field
Summer: F. Field
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.957 Practical Experience in Data Analysis
(, , , )
Prereq: None
Units arranged [P/D/F]
TBA.
For doctoral students in the Interdisciplinary Doctoral Program in Statistics participating in off-campus practical experiences in data analysis in programs where practical experience is accepted. Before registering for this subject students must have a training offer from a company or organization, must identify a research advisor, and must receive prior approval from the IDSS Academic Office. Upon completion of the experience, students must submit a letter from the company or organization describing the goals accomplished and a substantive final report to the MIT advisor discussing how data science and statistical tools were used during their experience and any interesting problems, applications, or results.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.960 Teaching in Data, Systems, and Society
(, , , )
Prereq: None
Units arranged [P/D/F]
TBA.
For Teaching Trainees in IDSS. Laboratory, tutorial, or classroom teaching under supervision of a faculty member. Restricted to doctoral students in IDSS who have completed requisite modules and training.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.961 Teaching in Technology and Policy
(, , )
Prereq: None
Units arranged [P/D/F]
TBA.
For Teaching Assistants in TPP, in cases where teaching assignment is approved for academic credit. Laboratory, tutorial, or classroom teaching under supervision of a faculty member. Credit for this subject may not be used for any degree granted by IDSS.
Fall: F. Field
IAP: F. Field
Spring: F. Field
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.970 Pre-Thesis Research in Data, Systems, and Society
(, , , )
Prereq: None
Units arranged
TBA.
For doctoral students defining their dissertation topic in IDSS. Covers all activities leading to an acceptable thesis proposal and approved for academic credit by the student's academic program. Includes identifying a research advisor and program planning. Culminates in a thesis proposal, approved by a complete doctoral committee, with working title, abstract, problem summary, significance, literature review, approach, timeline, and references. Academic advisor monitors student progress until a research advisor is identified. Restricted to doctoral students in IDSS.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
No textbook information available (IAP 2025); No required or recommended textbooks (Spring 2025)
IDS.971 Research in Technology and Policy
(, , )
Prereq: None
Units arranged [P/D/F]
TBA.
For research assistants in TPP when assigned research is not used for thesis, but is approved for academic credit. Credit for this subject may not be used for any degree granted by IDSS.
Fall: F. Field
Spring: F. Field
Summer: F. Field
No required or recommended textbooks
IDS.C35[J] Interactive Data Visualization and Society
(New)
()
(Same subject as 6.C35[J], 11.C35[J], CMS.C35[J])
(Subject meets with 6.C85[J], 11.C85[J], IDS.C85[J])
Prereq: None
Units: 3-4-8
Credit cannot also be received for 6.8530, 11.154, 11.454
Lecture: MW1-2.30 (45-230) Lab: R3 (45-102)
Covers the design, ethical, and technical skills for creating effective visualizations. Short assignments build familiarity with the data analysis and visualization design process. Weekly lab sessions present coding and technical skills. A final project provides experience working with real-world big data, provided by external partners, in order to expose and communicate insights about societal issues. Students taking graduate version complete additional assignments. Enrollment limited. Enrollment limited.
C. D'Ignazio, C. Lee, A. Satyanarayan
No textbook information available
IDS.C57[J] Optimization Methods
(New)
()
(Same subject as 6.C57[J], 15.C57[J])
(Subject meets with 6.C571[J], 15.C571[J])
Prereq: 18.C06 or permission of instructor
Units: 4-0-8
Introduction to the methods and applications of optimization. Topics include linear optimization, duality, non-linear optimization, integer optimization, and optimization under uncertainty. Instruction provided in modeling techniques to address problems arising in practice, mathematical theory to understand the structure of optimization problems, computational algorithms to solve complex optimization problems, and practical applications. Covers several examples and in-depth case studies based on real-world data to showcase impactful applications of optimization across management and engineering. Computational exercises based on the Julia-based programming language JuMP. Includes a term project. Basic competency in computational programming and linear algebra recommended. Students taking graduate version complete additional assignments. This subject was previously listed as 15.093/6.7200/IDS.200.
A. Jacquillat, H. Lu
IDS.C85[J] Interactive Data Visualization and Society
(New)
()
(Same subject as 6.C85[J], 11.C85[J])
(Subject meets with 6.C35[J], 11.C35[J], CMS.C35[J], IDS.C35[J])
Prereq: None
Units: 3-1-8
Credit cannot also be received for 6.8530, 11.154, 11.454
Lecture: MW1-2.30 (45-230) Lab: R4 (32-082)
Covers the design, ethical, and technical skills for creating effective visualizations. Short assignments build familiarity with the data analysis and visualization design process. Students participate in hour-long studio reading sessions. A final project provides experience working with real-world big data, provided by external partners, in order to expose and communicate insights about societal issues. Students taking graduate version complete additional assignments.
C. D'Ignazio, C. Lee, A. Satyanarayan
No textbook information available
IDS.S00 Special Undergraduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged
Opportunity for study of topics in Data, Systems, and Society not otherwise included in the curriculum. Offerings initiated by faculty on an ad hoc basis subject to IDSS approval.
Staff
IDS.S01 Special Undergraduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged
Opportunity for study of topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Consult IDSS Academic Office
IDS.S10 Special Undergraduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged [P/D/F]
Opportunity for study of topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.S11 Special Undergraduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: None
Units arranged [P/D/F]
Opportunity for study of topics in Data, Systems, and Society not otherwise included in the curriculum. Offerings initiated by faculty on an ad hoc basis subject to IDSS approval.
Staff
IDS.S20 Special Graduate Subject in Data, Systems, and Society
()
Prereq: Permission of instructor
Units arranged
TBA.
Opportunity for study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
C. Ortiz, E. Spero, J. Cohen
No textbook information available
IDS.S21 Special Graduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged
Opportunity for study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.S22 Special Graduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged
Opportunity for study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.S23 Special Graduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged
Opportunity for study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.S24 Special Graduate Subject in Data, Systems, and Society
(, )
Not offered regularly; consult department
Prereq: Permission of instructor
Units arranged
Opportunity for study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.S30 Special Graduate Subject in Data, Systems, and Society
()
Not offered regularly; consult department
Prereq: None
Units arranged [P/D/F]
Opportunity for study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.S31 Special Graduate Subject in Data, Systems, and Society
(, , )
Prereq: None
Units arranged [P/D/F]
TBA.
Opportunity for individual or group study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Fall: Staff
Spring: Staff
Summer: E. Milnes
No textbook information available
IDS.S32 Special Graduate Subject in Data, Systems, and Society
(, , , )
Not offered regularly; consult department
Prereq: None
Units arranged [P/D/F]
Opportunity for individual or group study of advanced topics in Data, Systems, and Society not otherwise included in the curriculum at MIT. Offerings are initiated by faculty on an ad-hoc basis subject to IDSS approval.
Staff
IDS.THG Graduate Thesis
(, , , )
Prereq: IDS.970 or permission of instructor
Units arranged
TBA.
Program of research, leading to the writing of an SM or PhD thesis to be arranged by the student with a member of the IDSS faculty. A minimum of 24 thesis units are required for the SM degree. Doctoral students must first complete IDS.970.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
Textbooks arranged individually
IDS.UR Undergraduate Research
(, , , )
Prereq: None
Units arranged [P/D/F]
TBA.
Undergraduate research opportunities in Data, Systems, and Society.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
Textbooks arranged individually
IDS.URG Undergraduate Research
(, , , )
Prereq: None
Units arranged
TBA.
Undergraduate research opportunities in Data, Systems, and Society.
Fall: E. Milnes
IAP: E. Milnes
Spring: E. Milnes
Summer: E. Milnes
Textbooks arranged individually
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