Im Jang-hwan's Kalman Filter 1

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 is the optimization theory required for AI/deep learning, computer vision, computer graphics, etc. Optimization Theory 1 mainly deals with the definition of multivariable functions and differentiation of multivariable functions. Why is that? Because all optimization problems are expressed in the form of multivariable functions. If you acquire the exact definition of multivariable functions and the concept of differentiation, the theoretical approach in the above fields will become considerably easier.

Master the linear algebra content required for AI/deep learning by investing 10 minutes a day and completing it in one month.

Master the linear algebra content required for AI/deep learning by investing 10 minutes a day and completing it in one month.

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

This is a lecture where you can easily learn important mathematical concepts used in games. People who are well-versed in mathematics take this knowledge for granted, so they cannot teach it assuming you know nothing. I explain from a beginner's perspective, truly assuming you are a non-major.

This course is for those preparing for the CosPro Level 1 exam, covering the COS Pro Level 1 sample problems released by the exam organizer, YBM Net Co., Ltd.

The most complete bible for passing all coding tests.

This is a hands-on course where you'll build an AI-based autonomous driving car using Raspberry Pi and various sensors.

This is a lecture on [Data Structure and Algorithm Core Theory & Related Practical Problem Solving] for IT company coding test preparation. - Python version -

Learn Python from scratch by fully utilizing ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly experiencing coding and developing problem-solving skills through example problems and practical exercises. After mastering Python's basic syntax, you can build your skills by solving various problems in Level 1 and Level 2. Furthermore, you can identify and supplement your weaknesses through an Exam structured like a real test. By regularly solving problems and utilizing ChatGPT, students can have a memorable learning experience without feeling bored.

Ruffle is an educational SW that makes it easier for students to learn SW using Python. Here, we will help you learn what you can do with SW and develop computational thinking skills through simple practice.

Strengthen your coding skills through coding test problems by learning Python-based data structures and algorithms!

Prepare perfectly for the Programmers Coding Essential Competency Certification (PCCE), from Python basics to competency certification!

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.

Baekjoon Bronze 3 Level Core Problem-Based Coding Test Fundamentals Training