Featured Spring 2025 Classes
6.2030 Electronics First Laboratory
Prereq: None. Coreq: Physics II (GIR)
Practical introduction to the design and construction of electronic circuits for information processing and control. Laboratory exercises include activities such as the construction of oscillators for a simple musical instrument, a laser audio communicator, a countdown timer, an audio amplifier, and a feedback-controlled solid-state lighting system for daylight energy conservation. Introduces basic electrical components including resistors, capacitors, and inductors; basic assembly techniques for electronics include breadboarding and soldering; and programmable system-on-chip electronics and C programming language. Enrollment limited.
Biology Undergraduate Seminars
A complete listing of the courses, instructors, and brief course descriptions is below. The topics are highly varied and encompass areas of genetics, genomics, biochemistry, molecular biology, cell biology, bacteriology, biophysics, microbiology, immunology, developmental biology, evolutionary biology, cancer biology, stem cells, infectious diseases, other human diseases, antibiotic resistance, chemotherapy, vaccines, bioengineering and biotechnology, and the search for extraterrestrial life.
These courses offer special features: small class size, a high degree of personal contact with the instructor(s), a focus on the primary research literature, and an opportunity to discuss current problems in biology interactively. These courses have two goals: first, to expose students to the kind of thinking that is central to contemporary biological research; and second, to impart specific knowledge in particular areas of biology.
10.00 Molecule Builders (6 units)
Think like a chemical engineer to brew the perfect cup of coffee or explore direct carbon capture! Subject 10.00 is an open-ended introduction to basic ChemE concepts: from reactor and biomolecular engineering to materials and energy systems. Teams will work to design and test interesting projects in a relaxed setting – yes, we tried making dog soap! The subject also satisfies a restricted elective in Course 10 for future students.
16.S690 Introduction to Autonomy
Prerequisites: Programming experience at the level of 6.100A (6.100L, the ASE, or demonstrated prior experience are acceptable)
Curious about programming autonomous robots? This course offers an alternative track for 6.100B that focuses on computational principles underlying autonomous systems. Our world increasingly relies on such systems, including for warehouse automation, self-driving/piloting vehicles, space and underwater operations, etc. To gain insight into how these systems work, we will cover fundamental modeling techniques and algorithms for making decisions. These include using graph search to plan, using probability to reduce uncertainty, leveraging optimization frameworks, and learning desired behavior from experience.
Compared to 6.100B, our topics are centered on decision-making rather than simulation and data science. However, we share the same goal of building confidence in programming for those who are relatively new to it, coming out of 6.100A or 6.100L. Exploring this track can help you preview if further courses in autonomy, such as 16.410, 16.405/6.4200, or 6.4110, would be of interest. In addition, taking this course will not limit you to robotics, as the techniques we cover are widely applicable in science, engineering, and even the arts.
Questions: Email intro-autonomy-staff@mit.edu
18.05: Introduction to Probability and Statistics
Pre-requisite: 18.02
The subject listing for 18.05 has just been updated to reflect a major evolution of the pedagogy and content over the last decade. Now, as a unified introduction to probability, Bayesian inference, and statistics, 18.05 satisfies requirements within many Courses (6, 7, 8, 9, 12, 14, 15, 18, 20, 22; with permission in others). This Spring, the course will expand to two sections to accommodate growing interest. Influenced by ESG, 18.05 is taught as a flipped course in a TEAL classroom to facilitate discussion, group problem solving, and coding studios with ample mentorship. Students also develop computational skills and statistical thinking by using R to simulate, analyze, and visualize data; and by exploring privacy, fairness, and causality in media and research on policy, genetics, health, and climate. Our students consistently report, and the data supports, that active learning enables more efficient and enjoyable growth. 18.05 is a common pre-requisite but designed to equip all students with skills and concepts to navigate an increasingly data-driven world. Contact Lecturer Jon Bloom (jbloom@mit.edu, Math and ESG) with any questions.
21.01 Compass: Love, Death and Taxes (CI-H)
The School of Humanities, Arts, and Social Sciences is offering a 12-unit, CI-H, introductory seminar listed as “Compass Course: Moral and Social Questions about the Human Condition.” Offered for the first time in spring 2025, it is co-designed and taught by professors from political science, philosophy, music, history, literature, linguistics, history, STS, economics, anthropology, CMS/writing, and cognitive science. It features a flipped classroom, experiential learning (including simulations, field trips, and debates), and engagement with diverse thinkers. You can learn more about the format, content, and motivation of the course at our website, compass.mit.edu.
Fast forward 25 years — sea levels rise, the media lies, democracy dies. Nothing is certain but love, death, and taxes. Have you made good decisions? Are you a good person? Do you know what is true? In this class, you will develop a compass to navigate a world full of challenges and complexity with insights from Beethoven, Dante, T. Chiang, LeGuin, Laozi, Kongzi (Confucius), Kuhn, Mill, J. Nagel, C.T. Nguyen, Plato, Rousseau, and more. The work will be done through a flipped, seminar style class taught by faculty across SHASS with debates, writing, and simulations.
ES.S70 Hack Yourself: Data-driven Wellbeing and Learning
Do you want to take charge of your wellbeing and learn at your best? In this seminar, you will discover how with practices based on positive psychology supported by data. At the end of the semester, you will have a toolkit of over 60 new habits plus some experience with data science tools you can use to “hack” yourself. Pre-req 6.100A or equivalent knowledge. Questions? E-mail pao@mit.edu