Topics in Mathematics with Applications in 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 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 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 a seminar on the philosophical analysis of film art, focusing on how films create meaning through their formal structures. Learners will explore aesthetic issues surrounding appearance and reality, as well as the effects of film technology on communication and alienation.

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 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 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 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 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 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 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 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 surveys the history of China from the first dynasty to the year 1800. It traces the rise of the world's first centralized bureaucratic state, the development of the world's oldest living written culture, and the formation of the pre-modern world's largest single commercial market.

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 hands-on workshop focuses on collaboration, design, and electronics prototyping using Arduino microcontrollers. Participants will engage in team-based projects, learning essential skills in programming, electronics, and project management, regardless of their prior experience.

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 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 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 builds on the foundations of programming in Python, emphasizing computational thinking and data science principles. Learners will explore how computation can effectively solve real-world problems, empowering them to write functional programs for various applications.

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 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.

_Project Laboratory in Mathematics_ immerses students in the world of mathematical research, allowing them to collaboratively tackle complex problems and present their findings. This course emphasizes teamwork and the exploration of mathematical concepts through hands-on projects.

This course is for those who want to study machine learning but lack statistical knowledge.

We will talk about the contents covered in general statistics lectures in a storytelling manner. You can use R, a free program, as easily as Excel, and easier than SPSS.

For those of you who are having a hard time with college statistics, a senior who was in the same position will share his know-how. Conquering basic statistics using R programming

This course is ideal for those who want to focus on theory and context rather than practice, aiming to organize their knowledge of deep learning in depth and grasp the big picture. It makes the mathematical and statistical foundations of deep learning easy to understand and provides intuitive interpretations of key modern models—such as AutoEncoder, GAN, Transformer, and AlphaGo—from a developer's perspective.