Topics in Mathematics with Applications in Finance

This course offers a hands-on, project-based introduction to building scalable and high-performance software systems. Learners will explore performance analysis, algorithmic techniques, and optimizations to effectively utilize modern computing platforms.

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 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 graduate course delves into the fundamental principles of Einstein's general theory of relativity, exploring topics such as differential geometry, black holes, and cosmology. Learners will engage with both the theoretical foundations and practical applications of general relativity.

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 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 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 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.

The Early Universe offers a comprehensive introduction to modern cosmology, exploring classical cosmology and the influence of contemporary particle physics on our understanding of the universe's origins.

Effective field theory is a fundamental framework for describing physical systems through quantum field theory. In this course, you will learn in depth about the general tools used in effective theories and Soft-Collinear Effective Theory (SCET) for hard interactions.

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 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 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 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 provides an introduction to analysis and aims to teach how to prove mathematical theorems and write proofs. It also covers how to rigorously prove the theorems of calculus.

This course surveys questions about human behavior and mental life, exploring topics such as perception, love, consciousness, and the nature of self. Students will engage with various theoretical perspectives, including biological, cognitive, and psychoanalytic, while experiencing psychology firsthand through demonstrations and discussions.

This course explores the practical aspects of proving that certain problems cannot be solved efficiently, focusing on reductions and techniques for demonstrating computational hardness across various complexity classes. Learners will engage with interesting problems and develop a deeper understanding of algorithmic limitations.

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 provides an introduction to cellular and population-level systems biology with an emphasis on synthetic biology, modeling of genetic networks, cell-cell interactions, and evolutionary dynamics. Learners will explore genetic switches, network motifs, and models of pattern formation.

This course covers key macroeconomic questions such as economic recessions, inflation, and fluctuations in unemployment rates. Learners will gain a deep understanding of government policies and the determinants of economic growth.

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 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.

Understand the essence of data visualization as a balance between scientific accuracy and aesthetic expression, and systematically learn everything from color and symbology principles to graph design. By utilizing visual attributes based on cognitive science principles, you will complete your data communication skills to achieve reliability and persuasiveness in professional practice.

Easy and powerful data analysis anytime, anywhere! Simple with Orange 3, even if you don't know how to code!

AI, the Key to Opening the World of Statistics "AI, by enabling easy mastery of complex statistical principles and analysis techniques, uncovers hidden meanings in data and provides insights for better decision-making. AI is now beyond a complex statistical calculator; it is a companion supporting statistical thinking."

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.

As the popularity and interest in AB Testing explodes, we will introduce Korea's first AB Testing lecture right now!

['Thought Architect' Roadmap for Translating Technical Truth into Business Value] 1. Introduction: Analysis of Constraints in Transferring Technical Truth to Business Value A significant bottleneck frequently observed across corporate sectors and engineering sites (R&D) is the phenomenon where innovative achievements, backed by massive resources and research capabilities, are discarded because they fail to overcome the 'communication threshold.' This is judged to stem from information asymmetry: a situation where management does not sufficiently perceive the depth of deep-tech, and technical personnel fail to appropriately utilize business language. This masterclass redefines the 'text-based communication competency' of engineers and scientists not as a mere administrative act of recording, but as part of a precise 'Engineering Design' process. Through this, we aim to present a mechanism by which an engineer's technical insights are transformed beyond simple records into core assets that drive the organization's strategic decision-making. 2. [Diagnosis] Analysis of Three Major Cognitive Defects Hindering Technical Communication ① Disconnection of Information Transfer due to the Curse of Knowledge This phenomenon occurs when experts become immersed in their own advanced level of knowledge and overlook the cognitive background of the information recipient. Consequently, reports centered on obscure formulas and technical acronyms are repeated, which is highly likely to result in structural losses such as loss of contact with decision-makers, delays in project approval, and failure in resource allocation. ② Value Loss due to Lack of Logical Architecture and Data Fragmentation By regarding document preparation as a simple post-hoc administrative procedure, errors of listing information without systematic design are frequently observed. These structural defects significantly damage the value of R&D achievements during the delivery process, tending to lead not only to the undervaluation of an individual engineer's capabilities but also to the loss of tangible and intangible assets for the entire organization. ③ Technical Reliability Crisis due to Deepening AI Dependency If generative AI, introduced to improve productivity, causes hallucinations without understanding the technical context, 'technical reliability'—the core value of engineering—can be seriously undermined. Utilizing AI without an accompanying logical verification system is highly likely to act as a potential system risk rather than a work efficiency tool. 3. [Prescription] Strategic Communication System for the Thought Architect ① Engineering Design of Thought for Unstructured Information A process of structuring abstract experimental data and hypotheses based on engineering system design principles is required. Bottom Line Up Front (BLUF): By placing core values and recommendations at the forefront of the document, we aim for an information structure optimized so that management can perform rapid and accurate decision-making (capital investment, mass production approval, etc.). Mutually Exclusive, Collectively Exhaustive (MECE): By adhering to principles that prevent logical overlap and omission, we ensure the logical completeness of the report by designing a seamless flow of thought. ② Global Standard Compliance and Quality Assurance Objectivity and integrity of data must be secured by internalizing standard protocols recognized by the global scientific community and global corporations. Standard Technical Reporting Structure (IMRaD): Maintain the consistency and reliability of the engineering narrative through a rigorous formal structure leading from Introduction, Methods, Results, to Discussion. 5 Principles of Sentence Quality (5C): By applying Correctness, Clarity, Conciseness, Consistency, and Completeness as quality control filters, we establish a Plain Language system that even non-experts can understand immediately. ③ S.E.E.D Prompt Architecture for Securing AI Command To operate AI not as a simple ghostwriting tool but as an assistant performing logical operations, a dedicated interface design must be involved. S.E.E.D Framework: Precisely control the quality of AI outputs by systematically structuring and inputting Situation, Expectation, Engineering Structure, and Data. Human-in-the-Loop: Establish a protocol where humans perform verification as the final approver to block the possibility of AI errors, thereby firmly maintaining technical authority. 4. [Execution] Strategies for Securing Cognitive Sovereignty and Workflow Optimization Communication competency acts as a core mechanism for preserving an engineer's cognitive functions beyond mere technical means. Responsibility-based Sandwich Workflow: Humans must perform context design (Top Bun) and final verification (Bottom Bun), delegating only the intermediate data processing (Meat) stage to AI to promote the activation of the human-unique Executive Control Network (ECN). RQTDW Learning Protocol for Knowledge Internalization: Apply the five stages of Read, Question, Think (facing contradictions), Discuss (virtual discussion), and Write to practical work to avoid simple acceptance of information and actively internalize knowledge. SIFT Model-based Precision Fact-Checking: Filter AI hallucinations and maintain technical precision through the process of Source (checking the origin), Investigate (understanding context), Find (cross-checking), and Trace. 5. Conclusion: Transition from Technical Expert to Engineering Leader The era of practitioners who simply perform given technical tasks is coming to an end. The ability to translate and communicate complex and difficult technical truths into a 'language of value' acceptable to organizations and society can be defined as a core survival strategy and a noble calling for modern engineers. Text communication is the Final Interface that projects an engineer's intellectual capacity to the outside world, beyond a simple act of recording. Through this masterclass, we expect you to prove your technical value and emerge as a powerful 'Engineering Leader' who drives organizational change. This system, which integrates 40 years of engineering insight, will become a strategic asset that completes your status as a professional.

ADsP Summary + Past Exam Solutions. Reflects August 2025 46th Exam! (Continuously Updated!)

This course covers the tools of probability theory and statistical inference, providing essential content for data analysis and understanding. Learners can acquire methods for utilizing data in various fields.

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 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.

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

ADsP Certification All-In-One Course! Ultra-Short Completion! Reference Book: "Everyone's ADsP Cheat Sheet" https://wikidocs.net/book/18829

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 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.

Learn multi-level data analysis using Structural Equation Modeling (SEM) bootstrapping techniques and Hierarchical Linear Modeling (HLM). This is an advanced course designed to help you grow into a statistical expert capable of analyzing complex research data, covering everything from advanced AMOS features to the practical application of HLM. You will master both theory and practice through real-world research cases in the fields of education, psychology, sociology, and health.

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

If you're wondering, "I did the user research... but is this result truly representative of all users?" then pay attention! We will show you exactly how to add persuasiveness to your designs based on data. ✅ We explain complex statistical terms in very simple language. ✅ We carefully introduce the 3 core hypothesis tests essential for UX practice, covering everything from principles to hands-on practice. ✅ We show you how to easily analyze user data using AI—without costs or hallucinations.

Feeling overwhelmed by where to start with complex data analysis? I will clearly guide you through how to utilize R and AI Tutors using the practical know-how I've built up.