Groundwater Hydrology

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 intricacies of poker theory and the application of poker analytics in investment management and trading. Learners will delve into decision-making frameworks and strategies that can enhance their understanding of both poker and financial environments.

This course delves into the intricacies of high-level programming language implementation, focusing on compiler design and optimization techniques. Learners will engage in a hands-on project that involves building a compiler in Java® that generates MIPS executable machine code.

This course focuses on learning several rules to improve speaking skills in important situations. Learners can master effective presentation methods for various contexts, such as interviews, thesis defenses, and oral exams.

This course presents an innovative approach to teaching linear algebra, focusing on key concepts and their interconnections. Learners will explore foundational topics and gain insights into the structure and applications of linear algebra through engaging video content.

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 provides a fast-paced introduction to deep learning, focusing on practical model-building for complex problems involving unstructured data. Learners will explore deep neural networks, convolutional networks, transformers, and generative models like ChatGPT and Midjourney.

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 delves into the critical issues of bias and fairness in machine learning, focusing on their implications for international development. Learners will explore strategies for the appropriate use of ML to promote equity and social justice.

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 examines the history of MIT through the lens of the broader history of science and technology, exploring its founding in 1861 and its evolution to the present day. Topics include educational philosophy, influential figures, and MIT's relationships with Boston, the federal government, and industry.

This course offers an immersive experience in the Japanese language, focusing on the simultaneous development of listening, speaking, reading, and writing skills. Learners will engage with authentic Japanese media to deepen their understanding of the language and culture.

This course explores the practical aspects of proving that certain problems cannot be solved efficiently, focusing on reductions and techniques for demonstrating computational hardness across various complexity classes. Learners will engage with interesting problems and develop a deeper understanding of algorithmic limitations.

This course covers the essential techniques for modeling and solving differential equations, which are fundamental in expressing the laws of nature. Learners will explore both the theoretical and practical aspects of differential equations, focusing on their applications in science and engineering.

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 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 introduces modeling and simulation techniques, focusing on continuum methods, atomistic and molecular simulation, and quantum mechanics. Learners will engage in hands-on training to apply these methods to significant engineering challenges.

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 intensive introduction to Old English (Anglo-Saxon), focusing on its grammar and literature, particularly the epic *Beowulf*. Learners will engage with prose texts, poems, and the foundational elements of this ancient language.

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 covers differentiation, integration, and vector calculus for multivariable functions. These mathematical tools and methods are used extensively in the physical sciences, engineering, economics, and computer graphics.

This course covers differential equations and the MATLAB® ODE suite in depth. Learners can understand the principles and applications of differential equations and develop problem-solving skills using MATLAB.

This course introduces non-equilibrium thermodynamic methods by briefly reviewing general thermodynamic concepts, multicomponent equilibrium properties, chemical equilibrium, electrochemical potential, and chemical kinetics. Through this course, an integrated understanding of phase equilibrium, transport, and non-equilibrium phenomena useful for energy and climate engineering technologies is provided.

This course includes demonstrations used to explain the theories and applications of lasers and optics. Learners can vividly observe and understand the fundamental phenomena of lasers.

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 role of government in the economy, applying tools of basic microeconomics to answer important policy questions. Learners will study various topics, including government responses to global warming, school choice, Social Security, and income tax rates.

This course covers the basics of signals and systems analysis, focusing on methods for representing discrete-time and continuous-time signals, as well as linear time-invariant systems. Students can apply these theories to various application fields such as feedback, control, communications, and signal processing.

This course introduces major approaches to symbol-based music theory and musicology. Learners will explore various topics, including music theory algorithms, music generation, and machine learning.

This course introduces students to the mathematical concepts and techniques essential in the financial industry, blending theoretical mathematics with practical applications. Learners will explore topics such as probability, statistics, and linear algebra, all within the context of finance.

This course covers numerical methods essential for solving complex problems in chemical engineering, including heat and mass transfer, fluid mechanics, and molecular simulation. Learners will explore various computational techniques and their applications in real-world engineering scenarios.