Engineering Dynamics

The one-year real-world record of a company that declared an “AI all-in” strategy. This case study introduces how DeNA, one of Japan’s leading IT companies, transformed an organization of 3,000 people into an AI-native company. For organizations preparing for an AI transformation, we’ve gathered only the most useful insights.

This course enhances kanji learning through engaging video lectures covering kanji characters from Tobira lessons 6–10. Students will learn not only how to write kanji but also the fascinating stories behind each character.

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 provides practical instruction in the design and analysis of non-digital games. Students cover the texts, tools, references and historical context to analyze and compare game designs across a variety of genres, including sports, game shows, games of chance, card games, schoolyard games, board games, and role–playing games.

This course explores the principles of feedback control in electronic and electromechanical systems, emphasizing its role in enhancing performance and reliability. Learners will engage with analytical concepts and practical applications through experiments and demonstrations.

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).

This course introduces the fundamental tools of game theory, the mathematical analysis of strategic interaction. Learners will learn how to use game theory to analyze various economic situations.

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 application of autonomy in real-world systems through the programming of cognitive robots. Learners will study advanced reasoning techniques and algorithms that enable robots to monitor themselves, schedule tasks, and collaborate with other agents.

This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis.

This course covers how to utilize video production skills to engagingly convey a passion for science, technology, engineering, and mathematics. Learners will have the opportunity to plan and conduct a 5-minute YouTube science program.

This course covers essential mathematical concepts widely used in mechanical engineering, focusing on linear algebra and ordinary differential equations (ODEs). Learners will explore numerical methods for solving systems of equations and apply these techniques to real-world engineering problems.

This course covers the essential steps to start a new venture, whether for-profit or social. Learners will explore the journey from idea inception to launching a successful business, including customer identification, business models, financial projections, and more.

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 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 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 explores the intersection of psychology and economics, focusing on behavioral economics and how human behavior diverges from traditional economic models. Learners will study recent advancements in the field and their applications across various economic sectors.

This course covers the foundations of mathematical analysis. You will study the convergence of sequences and series, continuity, differentiability, Riemann integration, sequences and series of functions, uniformity, and the interchange of limit operations.

This doctoral-level seminar delves into system dynamics modeling, emphasizing social, economic, and technical systems. Participants will engage with classic literature and contemporary research, critiquing and enhancing various models through hands-on 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.