인프런 - 라이프타임 커리어 플랫폼

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

The core of data science is expertly mimicking humans' ability to systematically analyze vast data! Through this process, you can refresh fundamental mathematical knowledge needed to understand scientific modeling, which forms the basis of data science.

You can understand the theoretical operation principle of the Kalman Filter through easy examples.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is essential to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence!

This course covers calculus at a first-year university level. In particular, it focuses on the integration of single-variable functions, allowing you to master various integration methods and technical approaches. As applications of integration, we will cover problems such as volume and surface area. You will also learn numerical integration methods using Python coding.

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

This is an in-depth linear algebra course for engineering majors in fields such as Machine Learning, AI, Robotics, and Computer Vision. It is recommended for those who wish to study linear algebra in depth. While explaining as simply as possible, it covers advanced topics through selective focus and concentration.

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.