Exploring Fairness in Machine Learning for International Development

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 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 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 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 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 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 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 is an introductory exploration of documentary film theory and production, focusing on documentaries about science, engineering, and related fields. Students engage in digital video production as well as social and media analysis of science documentaries.

This course delves into the visual representations of Japan's transformation into a modern state, focusing on its interactions with the world post-isolation. Learners will analyze historical images and media forms that reflect Japan's journey through significant events like the 1964 Tokyo Olympics and urban planning after WWII.

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 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 provides a comprehensive overview of the fundamental principles of biochemistry, genetics, molecular biology, and cell biology, with a specific focus on their applications in understanding human biology. Students will explore topics such as disease, developmental biology, neurobiology, and evolution, emphasizing biological functions at the molecular level.

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 introduces the dynamics and vibrations of lumped-parameter models in mechanical systems, focusing on kinematics, force-momentum formulations, and Lagrange's equations. Learners will also explore numerical methods and MATLAB® applications to solve dynamics and vibrations problems.

This capstone course focuses on integrating various disciplines of nuclear physics and engineering to tackle real-world design challenges in nuclear applications. Learners will engage in a group project to design a power plant that emphasizes emission-free electricity generation, carbon sequestration, and fossil fuel displacement.

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 introduces principles and technologies for converting heat into electricity via solid-state devices. Learners will explore thermoelectric energy conversion, thermionic energy conversion, photovoltaics, and solar thermal technologies, gaining insights into various solar heat collection systems and spectral control techniques.

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 explores the intersection of art and social responsibility, focusing on how intentional disruptions can challenge systems of oppression. Learners will engage with critical issues such as access to resources and the global water crisis through creative practices and pedagogical strategies.

This course examines the impact of new digital technologies on learning across various age groups and contexts. Students will explore educational technology through multiple lenses, enhancing their understanding of its opportunities, limitations, and implications for the future of education.

This course introduces the Reflective Practice approach developed by Donald Schön, focusing on how professionals can effectively combine their knowledge with practical situations. Learners will explore theories of learning and innovation to enhance their cognitive resources and improve their professional practice.

This course introduces machine learning in the medical field, covering the characteristics of clinical data and learning about risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and clinical workflow improvement through machine learning.

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 introduces quantitative approaches to understanding brain and cognitive functions. Learners will explore mathematical descriptions of neurons, their responses to stimuli, and foundational data analysis tools in neuroscience.

This course studies how the senses work and how physical stimuli are transformed into signals in the nervous system. It examines how the brain uses those signals to make inferences about the world, emphasizing audition and vision, while also discussing touch, taste, and smell.

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 explores the nature of intelligence, how the brain generates it, and how it can be replicated in machines. You will learn through an integrated approach that combines cognitive science, neuroscience, computer science, and artificial intelligence.

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 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 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 principles and applications of artificial intelligence, exploring its impact on various fields and society. Learners will study algorithms, machine learning, and ethical considerations surrounding AI technologies.

This course covers the content necessary to understand and create machine learning algorithms, specifically deep learning and neural networks, through linear algebra concepts. It provides a comprehensive explanation of linear algebra, including applications in probability, statistics, and optimization.