Essential Numerical Methods

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 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 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 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 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 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 critical issues of bias and fairness in machine learning, focusing on their implications for international development. Learners will explore strategies for the appropriate use of ML to promote equity and social justice.

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 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 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 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 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 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 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 the practical aspects of designing and analyzing non-digital games. Learners will explore various game genres while collaborating in teams to create, develop, and test original games, gaining insights into game mechanics and rules.

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 offers an immersive experience in the Japanese language, focusing on the simultaneous development of listening, speaking, reading, and writing skills. Learners will engage with authentic Japanese media to deepen their understanding of the language and culture.

This class provides some answers to basic questions about the nature of human language. Throughout the course, learners will examine how human language functions as a complex yet law-governed mental system, exploring topics such as language acquisition, historical language changes, and language endangerment.

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 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 is an intermediate algorithm course that focuses on efficient algorithm design and analysis techniques. Learners will master various algorithm design paradigms, such as divide and conquer, dynamic programming, and greedy algorithms.

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 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 covers the fundamental principles of finite element analysis for solving complex static and dynamic problems. Learners will learn how to implement finite element procedures for linear and nonlinear analysis.

This course is intended for students with little to no programming experience and focuses on understanding the role of computers in problem-solving. Students will build confidence in writing simple programs using the Python 3 programming language.

This course covers the practical impact that quantitative methods have had on today's most important companies. Learners will study key quantitative methods that create a competitive advantage, such as data mining, dynamic optimization, and simulation.

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 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 covers the fundamental principles of statistical mechanics, which takes a probabilistic approach to the equilibrium properties of large degrees of freedom. You will study various topics including thermodynamics, probability theory, and classical statistical mechanics.

This course is a collection of tutorial videos that visually explore various topics in materials science and engineering. Learners will discover how to use the Wolfram Mathematica programming system to easily understand complex concepts.

This course connects algorithmic puzzles with computer programming, teaching students to code while solving engaging challenges. Learners will explore Python syntax and semantics as they tackle various puzzles, enhancing their programming skills in a fun and practical way.

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 major approaches to symbol-based music theory and musicology. Learners will explore various topics, including music theory algorithms, music generation, and machine learning.