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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 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 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 introduces computational methods for solving physical problems, particularly in nuclear applications. Learners will study differential equations, numerical approximations, and various techniques for simulating particle behavior and conservation problems.

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 course is an introduction to the process of generating a symbolic description of the environment from an image. It covers the physics of image formation, image analysis, binary image processing, and filtering, with applications in robotics and intelligent machine interaction.

This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. Learners will study essential concepts in probability and statistics, along with modern data analysis techniques such as regression, econometrics, and data visualization.

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.

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 the structural principles of digital systems and introduces architectures commonly applied across various technologies. Learners will cover a wide range of topics, including multi-level implementation strategies, the definition and mechanisms of new primitive elements, and performance measurement.

"How is a 1-trillion parameter model trained?" Discover the scaling strategy of Kimi K2.5, revealed directly on stage by Moonshot AI at GTC 2026, in Korean on Inflearn. 2x token efficiency · 1 million token context · 1,000 agent swarm The next step for open-source LLMs is here. * This lecture is released for free through an official collaboration between Moonshot AI, the creator of Kimi, and Inflearn.

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 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 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.

Functional analysis explores the study and resolution of linear and nonlinear problems in normed spaces, extending beyond finite dimensions. Learners will delve into key concepts such as normed spaces, completeness, functionals, and the Spectral Theorem, gaining insights applicable to various mathematical and physical contexts.

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.

This course covers the basics of electrical engineering and electronic circuits, teaching the fundamental principles required for electronic system design. Students will explore various topics, including resistive elements, switches, MOS transistors, and analog and digital circuits.

This course immerses learners in an artificial intelligence programming contest where teams create virtual robots to compete in Battlecode, a real-time strategy game. Participants will enhance their programming skills through hands-on experience and optional lectures on relevant topics.

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.