[Free] Python Basics You Must Learn Before Learning Python

If you're planning to learn C language, pay attention to this lecture!!! It's completely free~ I highly recommend it for preliminary study before taking formal courses or individual learning.

Based on over 100 deep learning training sessions, this course systematically organizes the core foundational theories that students found most challenging. The course connects mathematical intuition, model learning principles, and code implementation step by step in a way that even non-majors can understand, deeply covering the fundamental structure and operating principles of how AI models learn, rather than just library usage. This is a practical introductory course designed to help you grow into a skilled engineer who understands AI principles by implementing core deep learning foundational technologies such as gradient descent, loss functions, optimization, perceptrons, multilayer neural networks, and backpropagation through both formulas and code.

Anyone can easily create a Python game using the Pygame library, starting from zero base.

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

Learn the basic grammar of the Python language, practice writing simple logic using it, and learn about various libraries.

For those who want to learn data science, big data, and web crawling, (1) we summarize the most essential Python syntax in a short time, and (2) you'll become familiar with Python and crawling through practical crawling programming.

We understand why Attention was needed and how it works by 'implementing it directly with code'. This lecture starts from the structural limitations of RNN and Seq2Seq models, experimentally verifies the information bottleneck problem and long-term dependency issues created by fixed context vectors, and naturally explains how Attention emerged to solve these limitations. Rather than simply introducing concepts, we directly confirm RNN's structural limitations and Seq2Seq's information bottleneck problems through experiments, and implement **Bahdanau Attention (additive attention)** and **Luong Attention (dot-product attention)** one by one to clearly understand their differences. Each attention mechanism forms Query–Key–Value relationships in what way, has what mathematical and intuitive differences in the weight calculation process, and why it inevitably led to later models naturally connects to their characteristics and evolutionary flow. We learn how Attention views sentences and words, and how each word receives importance weighting to integrate information in a form where formula → intuition → code → experiment are connected as one. This lecture is a process of building 'foundational strength' to properly understand Transformers, helping you deeply understand why the concept of Attention was revolutionary, and why all subsequent state-of-the-art NLP models (Transformer, BERT, GPT, etc.) adopt Attention as a core component. This lecture is optimized for learners who want to embody the flow from RNN → Seq2Seq → Attention not through concepts but through code and experiments.

Leverage Python to learn machine learning techniques, improving real data information extraction and prediction model development skills!

"Following trends is important, but unwavering fundamentals create real skills" This course is an introductory program that helps you understand the flow of data science and properly learn the most practical techniques first.

The first class in the curriculum, "Anyone Can Learn Python", is an introductory programming course for those with no programming/coding experience. Based on my experience with numerous classes taught to non-majors, this class focuses on the "story" and "principles" from the structure of a computer to how programs work and the role of programming languages in this process, allowing beginners to approach the unfamiliar concept of programming more familiarly. In addition, by adopting the Python language, which has recently been growing at an incredible rate, the barrier to entry for programming has been lowered even further, and when explaining the grammatical elements of the language, the focus is on "Why" and "How" rather than "What", so that it is not a simple grammar memorization class, but rather on real-world examples and practical applications. Based on the incorrect learning methods that beginners often use, it also covers tips on how you should view and learn programming in the future, and based on the trial and error I experienced while struggling and wasting time while teaching programming on my own in the past and the inner strength I gained from conducting offline classes for many years, it focuses on what beginners find difficult and how to convey it, so it will be of great help to those who are hesitant about getting started with Python.

AI that thinks and adapts? Now you can build it yourself. Master the core of reinforcement learning with intuitive explanations and code, not complex theories, and grow into a 'practical developer' through finance and industry projects.

You can quickly convert MATLAB code to PYTHON by extracting only the PYTHON grammar that matches the MATLAB grammar.

Coding Test [ALL IN ONE] ✔️ Complete with one lecture

During our school days, the 'click' sound we heard in the computer lab... that was Minesweeper. In this course, we'll recreate those memories by implementing it with Python. Whether you're a beginner or even someone encountering Python for the first time, by following along line by line, you'll find that your very own Minesweeper game has been completed before you know it.

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

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

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

Learn Python coding. Learn design scripting with Rhino3d Grasshopper. Learn creative coding such as computational thinking, parametric, and generative design.

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

Do you manually type in numerous commands every time you build a complex project or create a deployment package? Currently, most open-source projects use build automation scripts to save the trouble of typing commands. Do you also find building tedious? Then use this course to automate your builds and increase your work efficiency.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.