Collaborative Design and Creative Expression with Arduino Microcontrollers

This course focuses on the design and implementation of secure computer systems, exploring various threat models and security techniques. Learners will engage with topics such as operating system security, network protocols, and hardware security, drawing insights from recent research papers.

This course explores the fundamental role of data structures in computer science, emphasizing their importance in developing efficient algorithms. Learners will study advanced topics, including dynamic graphs, memory hierarchy, and hashing, while engaging with current research directions in the field.

This course explores the evolution of proofs in computer science, focusing on interactive proofs, multi-prover interactive proofs, and probabilistically checkable proofs. Learners will discover how to leverage cryptography to transform these advanced proof systems into computationally sound non-interactive arguments (SNARGs).

This course provides a comprehensive introduction to systems engineering, focusing on both classical and modern approaches. Learners will explore key concepts such as stakeholder analysis, requirements definition, system architecture, and design optimization, applying these principles to real-world projects.

This course examines the choices and constraints regarding sources and uses of energy by households, firms, and governments through a number of frameworks to describe and explain behavior at various levels of aggregation. Examples include a wide range of countries, scope, settings, and analytical approaches.

This course covers key topics in discrete applied mathematics, focusing on counting, generating functions, probability, and more. Learners will engage with both mathematical concepts and effective communication through writing assignments.

This course explores how financial technology, or FinTech, is transforming the financial services industry through innovative technologies. Learners will study key trends such as AI, blockchain, and open APIs, gaining insights into the evolving market landscape and regulatory environment.

This course builds on the foundations of programming in Python, emphasizing computational thinking and data science principles. Learners will explore how computation can effectively solve real-world problems, empowering them to write functional programs for various applications.

This course delves into the essential concepts of matrix calculus, focusing on its applications in machine learning and large-scale optimization. Learners will explore techniques to understand and compute derivatives of matrices and their factorizations, enhancing their ability to tackle complex mathematical operations in modern computing.

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas.

This course covers the fundamentals of deep learning, including both theory and applications. Topics include neural net architectures (MLPs, CNNs, RNNs, graph nets, transformers), geometry and invariances in deep learning, backpropagation and automatic differentiation, learning theory and generalization in high dimensions, and applications to computer vision, natural language processing, and robotics.

This course explores the mathematical concepts and techniques essential for the financial industry, blending theoretical mathematics with practical applications. Learners will study topics such as linear algebra, probability, statistics, and stochastic processes, guided by both MIT mathematicians and industry professionals.

This course covers elementary discrete mathematics for science and engineering, focusing on mathematical tools and proof techniques useful in computer science. Learners will explore topics such as logical notation, sets, relations, graph theory, state machines, and algorithms.

This course emphasizes dynamic models of growth and development, exploring topics such as migration, modernization, and technological change. Learners will study the interplay between economic theory and real-world applications in developing countries, focusing on income distribution, institutional change, and the functioning of financial markets.

This course explores the fundamental principles of artificial intelligence, focusing on both theoretical concepts and practical applications. Learners will study algorithms, machine learning techniques, and the ethical implications of AI technologies.

This course equips learners with the essential knowledge and skills for teaching science and engineering at the college level. Participants will explore innovative teaching methods, engage in active learning, and develop their own teaching practices through research and presentations.

This course provides an introduction to chemical oceanography, focusing on the composition and dynamics of seawater and the biogeochemical cycles that shape oceanic environments. Learners will explore key concepts such as reservoir models, nutrient cycling, and the impact of human activities on ocean chemistry.

This course explores the integration of architectural design within natural landscapes, focusing on the relationship between built environments and their ecological contexts. Learners will develop skills in analyzing landscape and climate to inform their design decisions through drawings and models.

This course focuses on developing innovative information systems tailored for resource-poor settings, aiming to enhance health outcomes and strengthen organizational infrastructures. Learners will explore the intersection of public health, technology, and collaborative ecosystems to address healthcare challenges in developing countries.

This course is an introduction to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality.

This course goes beyond simple kit assembly; it is a process of building the open-source project Otto DIY from scratch. We have included everything from the secrets of component selection and hardware operating principles to Arduino coding (functions, variables, loops), and even the troubleshooting know-how for voltage drops, which beginners find most challenging. Don't just stop at theory—develop the skills of a 'true robot maker' by completing your own smartphone-controlled robot!

This course provides an integrated introduction to electrical engineering and computer science, learning through experiments using mobile robots. It aims to understand and utilize the fundamental design principles of modularity and abstraction in various contexts.

AI Finally Gets a Body - What is My Survival Strategy in the Age of Robots? Physical AI is not just about robots. It is an overthrow of the economic paradigm created by the grand convergence of artificial intelligence, robotics, and energy technology. This course explores various perspectives, from the background of Physical AI's emergence to the strategies of global big tech, hardware sovereignty, and future social issues such as robot taxes, basic income, and global inequality.

In this course, you will learn the basics of photography and gain an exciting new perspective on the visual world. While the focus is on science and engineering photography, most of the content can be easily applied to other types of macro photography.

D-Lab: Energy provides a hands-on, project-based learning experience focused on small-scale, sustainable energy technologies in developing countries. Students will engage in practical projects that include the design, construction, and evaluation of energy systems such as micro-hydro, solar, and wind turbines.

This course delves into the fundamental principles of front-end processes essential for fabricating devices in silicon integrated circuits. Learners will explore advanced physical models and practical aspects of key processes such as oxidation, diffusion, ion implantation, and epitaxy, alongside emerging materials like Silicon Germanium (SiGe).