인프런 - 라이프타임 커리어 플랫폼

Now is the time to answer based on data rather than experience! If you quantify the reliability with statistical knowledge and present it as evidence, your persuasiveness will increase infinitely!

Anyone who likes math, raise your hand! Anyone who wants to learn probability and statistics, raise your hand!

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. :)

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

This course is designed to help those who want to deeply organize deep learning and grasp the big picture by focusing on theory and context rather than hands-on practice. You can easily understand the mathematical and statistical background that forms the foundation of deep learning, and gain an intuitive interpretation from a developer's perspective of the principles behind major modern deep learning models such as AutoEncoder, GAN, Transformer, and AlphaGo.

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.

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.

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.

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

We will talk about the contents covered in general statistics lectures in a storytelling manner. You can use R, a free program, as easily as Excel, and easier than SPSS.