Classes
Subject Listings
Please visit the Registrar’s Subject Listing for a searchable, comprehensive, and up-to-the-minute list of our offered classes.
EAPS also maintains a running spreadsheet of class offerings along with a 4-year projected subject plan. Disclaimer: this subject plan can change frequently and should be considered as a tentative, unofficial guideline only. The further out the subject occurs, there may be more uncertainty.
Please note that the MIT-WHOI Joint Program manages the classes offered within their program. The courses listed in the Registrar’s subject listing and the EAPS 4-year subject plan are based on the information we have received to date. The most reliable source for MIT-WHOI Joint Program information is the Joint Program classes web page.
Questions? eaps-ed-office@mit.edu
How to Register
Visit WEBSIS to register for courses. Please pay close attention to the MIT Academic Calendar to make sure you are aware of deadlines and avoid late fees.
Below, you will find a schedule of the courses for each term.
EAPS does not offer courses during the Summer term other than those required for undergraduate and graduate thesis enrollment and those associated with the Undergraduate Research Opportunities Program (UROP).
EAPS offers a variety of courses using Special Topics subject numbers. They appear with an “S” in the subject listing (eg. 12.S590). The MIT subject listing will represent these as a generic description because the subject is considered a “repeating” course number. These courses may have different specialized topics within the discipline each term. Specific information on each subject from the last two academic years can be found below. Please refer to the MIT subject listing for up to date information on these courses. “Units arranged” means the student arranges the number of units with the instructor.
Fall 2024
12.S680/12.S681 Special Topics in Planetary Science: Exoplanet Atmospheres
Description: This is a project-based class where each student will choose a small research project in exoplanet atmospheres to complete during the course. JWST proposals can be included as a project. Instruction will cover fundamentals needed to pursue the research project, possibly including transmission, reflection, and emission spectroscopy, molecular cross sections, equilibrium chemistry, 1D temperature structure, cloud formation, and telescope noise. Students will gain a working knowledge of exoplanet atmospheres as well as a practical set of computer simulation tools via publicly available codes.
Instructor: S. Seager
Level: G
Units: 6
12.S592 Special Seminar in Earth, Atmospheric and Planetary Sciences
There is extraordinary interest in Machine Learning across Science and Engineering that traditionally has heavily relied on theory to develop models for prediction and discovery. However, many aspects of how to couple data-driven approaches (that ML is based on) and theory-driven approaches (that much of science and engineering is based on) must be better understood in a rapidly developing field. In this seminar, we will study the many ways “theory-driven” (such as with the availability of governing equations) and “data-driven” (e.g., through statistical or deep learning) approaches have been coupled to understand where the optimal combination might be, particularly, for the earth, atmospheric, and planetary applications. The primary material will be drawn from current literature presented by authors and students and supplemented with in-class lectures to dive deeper into the methodology, investigating its value using a stochastic process and information-theoretic perspective. The seminar includes reading papers, discussion in class, and finishing a project or three PSETs. In this new offering, topics emerging within several grand climate challenge areas are emphasized. However, variations are possible. So, please come to the first two classes, where the topics will be set based partly on participant interest and experience. The course is geared towards students with an engineering, science, or mathematics background and initial exposure to machine learning.
Instructor: S. Ravela
Level: G
Units: Units arranged
Spring 2024
12.S680, 12.S681 Special Seminar in Planetary Science: From Grains to Gas Giants-The Formation of Planetary Systems
Through reading and class discussions, students explore the physical and chemical processes which grow small interstellar dust grains to the super-Jovian planets common in outer space which set the stage for the origins of life. Students will investigate how planetary systems form and which factors are most influential during this process. Specific topics include: the thermophysical and chemical structure of protoplanetary disks, grain evolution, planet-disk interactions, atmospheric accretion, and astronomical observations. Students are required to synthesize information, develop analytical and critical skills in paper reading and writing. 12.S680 is letter-graded.
Prereq: Permission of instructor.
Instructors: R. Teague, B. Weiss
Level: G
Units: 6
IAP 2024
12.S590 Special Seminar in Geophysics: The Energy Transition Challenge for Geosciences
The ‘Geosciences and the Energy Transition Challenge‘ course provides the participants with a broad understanding of technical, economic, and societal issues relevant to subsurface energy resource developments. For instructional purposes we will work on carbon storage (CCS), geothermal, and hydrocarbon extraction examples, and consider a range of various production/use scenarios in the context of impact: carbon-free, -neutral and -negative production/use scenarios.
Emphasis is on practical work and involves the assessment and development planning of a geothermal project, a carbon sequestration store, and a hydrocarbon field. The participants analyze hands-on practical and realistic examples that involve technical and basic economic evaluations; risks and uncertainties; dilemmas and stakeholder expectations, and wider socio-economic challenges related to developing an industrial scale subsurface energy resource.
The participants will interpret some basic technical data, create production- and cashflow profiles, take on technical and non-technical challenges, and think about the feasibility and risks of subsurface energy projects from technical, economic, and societal perspectives. By the end of the course the participants will present a development plan for an underground energy resource covering all aspects addressed during class thereby demonstrating an understanding of the complexities involved in the energy transition.
Also, the contributions of these case study projects are placed in the context of the energy system and of the Paris Climate goals to get an appreciation of the scope of the challenges that lie ahead.
This course is set-up for teamwork and is designed using a problem-based learning approach. Learning is through a blend of lectures (5 lecture sessions, 3 hour each) covering the basics of subsurface resource development, practical team-work modules (4 afternoons), and class discussions of interim results. No prior subsurface experience is required.
Instructor: R. Franssen, E. Hoogerduijn-Strating
Level: G
Units: 3
12.S592 Special Seminar in Earth, Atmospheric and Planetary Sciences
There is extraordinary interest in Machine Learning across Science and Engineering that traditionally has heavily relied on theory to develop models for prediction and discovery. However, many aspects of how to couple data-driven approaches (that ML is based on) and theory-driven approaches (that much of science and engineering is based on) must be better understood in a rapidly developing field. In this seminar, we will study the many ways “theory-driven” (such as with the availability of governing equations) and “data-driven” (e.g., through statistical or deep learning) approaches have been coupled to understand where the optimal combination might be, particularly, for the earth, atmospheric, and planetary applications. The primary material will be drawn from current literature presented by authors and students and supplemented with in-class lectures to dive deeper into the methodology, investigating its value using a stochastic process and information-theoretic perspective. The seminar includes reading papers, discussion in class, and finishing a project or three PSETs. In this new offering, topics emerging within several grand climate challenge areas are emphasized. However, variations are possible. So, please come to the first two classes, where the topics will be set based partly on participant interest and experience. The course is geared towards students with an engineering, science, or mathematics background and initial exposure to machine learning.
Instructor: S. Ravela
Level: G
Units: Units arranged
Fall 2023
12.571 Seminar in Geophysics
Students will engage with invited speakers on a variety of cutting-edge topics within geophysics. Invited speakers from New England and beyond will come to give seminars every two weeks throughout the semester. Prior to the speaker’s visit, students will read papers provided by the speaker so that students can engage with the material before the speaker’s visit through student-led discussion. During their visit, speakers will engage with students during both 1:1 meetings and a discussion wit students following the seminar.
Instructor: W. Frank
Level: G
Units: 6
12.S501: Special Seminar in Earth, Atmospheric and Planetary Sciences
Familiarizes graduate students with the research of visiting EAPS DLS speakers and provides opportunities for student networking with speakers. Enrolled students are expected to attend most DLS seminars (scheduled weekly) as well as meet with the speakers to discuss their research. In preparation for each visiting speaker, students read one assigned paper showcasing the speaker’s presented work, and collectively draft a set of questions/topics to be discussed.
Instructor: Greg Fournier
Level: G
Units: 3
12.S592: Special Seminar in Earth, Atmospheric and Planetary Sciences
There is extraordinary interest in Machine Learning across Science and Engineering that traditionally has heavily relied on theory to develop models for prediction and discovery. However, many aspects of how to couple data-driven approaches (that ML is based on) and theory-driven approaches (that much of science and engineering is based on) must be better understood in a rapidly developing field. In this seminar, we will study the many ways “theory-driven” (such as with the availability of governing equations) and “data-driven” (e.g., through statistical or deep learning) approaches have been coupled to understand where the optimal combination might be, particularly, for the earth, atmospheric, and planetary applications. The primary material will be drawn from current literature presented by authors and students and supplemented with in-class lectures to dive deeper into the methodology, investigating its value using a stochastic process and information-theoretic perspective. The seminar includes reading papers, discussion in class, and finishing a project or three PSETs. In this new offering, topics emerging within several grand climate challenge areas are emphasized. However, variations are possible. So, please come to the first two classes, where the topics will be set based partly on participant interest and experience. The course is geared towards students with an engineering, science, or mathematics background and initial exposure to machine learning.
Instructor: Sai Ravela
Level: G
Units: Units arranged
12.S992: Special Subject in Climate Science
Provides students with knowledge of statistical concepts necessary for rigorous analysis of the frequency, duration, and magnitude of extreme events. Topics include data types encountered in statistical analysis of climate extremes (event times, peaks over threshold, block extremes) as well as probability distributions most often used to describe them (generalized extreme value, generalized Pareto, Poisson); persistence models and stochastic processes; compound events; and analysis methods (bootstrapping, maximum likelihood estimation, Bayesian analysis). It is expected that students have coding experience (e.g., MATLAB, Python, Julia, R). Undergraduate coursework (or equivalent) in calculus and probability is also recommended but not required. The students will come away from the class equipped to critically engage the literature on the topic, to perform extreme value analysis in their own research, and to speak knowledgably on the scientific basis of our current understanding of extreme events in a warming world. This course is intended to be taken by students concurrently enrolled in 12.757 Climate Change Science: Extreme Events in a Warming World, but other students may be allowed to enroll at the discretion of the instructor. Textbook: Statistical Analysis of Climate Extremes, Manfred Mudelsee, Cambridge, 2020.
Instructor: Chris Piecuch (WHOI)
Level: G
Units: 6
You’ll find select EAPS subjects and course materials hosted on various open-access platforms.
