Introduction to Algorithms

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 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 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 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 explores the design and functionality of Bitcoin and other cryptocurrencies, emphasizing cryptography, game theory, and network architecture. Learners will engage with practical programming assignments to deepen their understanding of these evolving systems.

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 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 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 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 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 explores the transformative potential of blockchain technology in the realms of money and finance. Learners will study the fundamentals of blockchain, distributed ledgers, and smart contracts, with a focus on current and future applications in the financial sector.

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 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 delves into complex variables, differential equations, and linear algebra, providing a comprehensive understanding of these essential mathematical concepts. Learners will explore foundational theories and applications that are crucial for advanced studies in mathematics and engineering.

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 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.

"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 covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics, social sciences, natural sciences, and engineering. It parallels the combination of theory and applications in Professor Strang’s textbook Introduction to Linear Algebra.

This course explores the interdisciplinary field of assistive technology, focusing on designing solutions that enhance the independence of individuals with disabilities. Learners will engage in hands-on projects, collaborating with clients to create innovative devices and applications.

This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Learners will study key concepts such as stability, performance measures, and design methods essential for effective control system implementation.

This course introduces the mathematical modeling of computational problems. It covers common algorithms, algorithmic paradigms, and the data structures used to solve these problems.

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.

The core of software development ultimately lies in 'how quickly data can be found and processed.' Among numerous algorithms, the Hash Table is an essential tool that forms the foundation of modern programming languages and system architectures. This lecture goes beyond simple theoretical explanations to cover how students can 'immediately' resolve specific performance bottlenecks encountered in practice using hash tables.

Through this course, you can systematically learn core concepts such as Basic Sorting Algorithms, Advanced Sorting Algorithms, Special Purpose Sorting Algorithms, and Practical Considerations.

Through this lecture, you can systematically learn core concepts such as the basic concepts and characteristics of queues, fields of application, problem-solving strategies, practical example code (Python), and advanced queue utilization techniques.

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 covers fundamental discrete mathematics for computer science and engineering. It focuses on mathematical definitions, proofs, and applicable methods, covering various topics such as logic symbols, proof techniques, sets, relations, and graph theory.

This course provides an interactive introduction to discrete mathematics for computer science and engineering. Learners will study fundamental mathematical concepts, discrete structures, and discrete probability theory, developing the ability to apply these to various fields of computer science.

For learners just starting programming, C can feel difficult because of unfamiliar concepts such as variables, operators, conditional statements, loops, functions, arrays, and pointers. This course is an introductory C programming course taught directly by Professor Chang-Hyun Lee, the author of *C Language on My Own* and a developer with 25 years of experience. Rather than simply memorizing C syntax, the course explains step by step why each piece of syntax is needed, how it works in a program, and how to solve real-world problems with code. Starting with the fundamental concepts of programming, you will learn the core basics of C one by one, including variables and data types, operators, conditional statements, loops, functions, arrays, and pointers. Assignments for each part also provide hands-on experience writing code and solving problems using what you have learned. Drawing on 25 years of experience in development and education, this course guides beginners in C programming so they can build a solid foundation in the fundamentals of programming.