인프런 - 라이프타임 커리어 플랫폼

This course will help you build your knowledge of the fundamentals of integration of multivariable functions.

This course covers introduction to linear algebra, and you can master introduction to linear algebra through the lectures.

This lecture is designed to provide a foundation in middle and high school mathematics for adults who gave up on math during their school years but are now looking to tackle engineering mathematics.

Understand machine learning concepts, AI learning principles, and mathematical principles for model implementation to fully utilize deep learning!

This lecture is a lecture that only extracts the core of set theory. Starting with this lecture, you can start various mathematics such as linear algebra and calculus without any difficulty.

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

Let's build a foundation of MATLAB and apply and understand the basic concepts of programming!

Learn why Propensity Score Matching analysis is so popular and what its advantages are. Also, use it to easily create tables and graphs that can be used immediately when submitting a paper.

Statistics learned in school, was it too hard to understand? No matter how much you listened to the explanation, statistics were confusing, but we will help you understand them. If you implement them one by one by hand using Excel, you will understand statistical concepts that you didn't understand! A new experience that makes boring statistics fun! We will give you a gift. :)

Attention to those who want to study stocks! But, you are studying stocks without knowing financial engineering? How about learning how to make money properly through financial engineering from the basics?

Were you a math-phobe during your school days? It's said that math is important in AI, but do you feel lost on how to approach it? The reason math is important in AI is because math is used in the computational processes of AI (Machine Learning and Deep Learning). For easy explanations of differentiation, linear algebra, and probability and statistics to understand AI, it is structured with simple explanations using graphs (coordinates) rather than mathematical derivations.

If calculus is too difficult? From the basics, step by step! Covers university-level calculus.

It's an undeniable fact that mathematics is essential for game developers. Instead of excessively deep traditional math lectures, learn all the mathematical techniques you can use right away!

The core of all AI/deep learning is ultimately optimization. Of course, optimization theory is not only needed in AI/deep learning. Computer vision, robotics & control systems, financial engineering & quant, data science, signal processing... Probably no matter which field you study, optimization theory is one of the topics you will inevitably encounter when you go deeper. This lecture systematically covers everything from basic mathematical theory to in-depth content. I believe it is by far the best optimization theory lecture offered in Korea.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

How should we integrate the results of different diagnostic methods when they are different? Are there any diagnostic methods that are unnecessary among the various diagnostic methods? We will provide answers to these questions.

For those who are interested in game development and know that math is important, but don't know what math to study, I've prepared a lecture that provides a general explanation. I want to talk about the various maths used in the game production process.

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

This course will help you build your knowledge of advanced integration of multivariable functions.

Theory, numerical approximations, intuition, and visualization in integral calculus. Enhance your math-coding skills.