Getting Started with MATLAB

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

Let's acquire the Python coding skills necessary for artificial intelligence by learning the basics of the Python programming language!

Let's design, implement, and develop while learning the basic and object-oriented concepts of the C++ language!

Let's build a solid foundation in Python and solve data analysis problems!

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

Let's understand the major algorithms of machine learning and deep learning, and get to know artificial intelligence!

Let's develop data-driven administrative practical skills to empirically solve administrative and policy problems by analyzing public data with R and Python!

Let's learn various data structures and algorithms and develop practical skills by implementing them through programming!

It improves logical thinking skills, fosters the ability to understand how to use programming tools, and develops the capacity to design algorithms for problem-solving.

Let's understand machine learning and deep learning model algorithms by using Keras!

ChatGPT, become a creator using generative AI!

Let's have fun coding with various cute robots using artificial intelligence!

Let's build the skills to develop web applications using React and cultivate the capability to apply them in practice!

Let's develop the capacity to extract valuable information from big data and support decision-making!

Let's learn how to use Git and GitHub and use them for collaboration!

Let's understand data analysis methods using Python, analyze and visualize various types of data on our own, and organize an outline of our data story!

Experience text-based coding through block coding and let's control an Arduino!

Let's cultivate professional expertise in programming, algorithms, and statistical analysis!

Let's create your own self-driving car using block coding using Scratch Entry!

It improves logical thinking skills and cultivates the capacity to converge one's major with information and communication technology in the era of the Fourth Industrial Revolution.

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

This is optimization theory required for AI/deep learning, computer vision, computer graphics, and more. Optimization Theory 1 focuses primarily on the definition of multivariable functions and their derivatives. Why is that? It is because all optimization problems are expressed in the form of multivariable functions. If you acquire an accurate definition of multivariable functions and the concept of differentiation, the theoretical approach to the aforementioned fields will become significantly easier.

We foster capabilities to prepare for future technological changes by learning from the basics related technologies that are at the core of 4th Industrial Revolution technologies, such as ICBM (IoT, Cloud, Big Data, ML), autonomous vehicles, and the metaverse.

This is a basic machine learning course for those who don't know math and coding well, but want to understand machine learning trends and utilize machine learning technology to plan products.

- I am a Research Engineer/AI PM running a 4-year-old AI startup. - This video is a lecture for those who want to start studying artificial intelligence "now" or in "2026". - Looking at college students, I see many who have no idea how to get started with artificial intelligence. - I hope that after watching this lecture, you'll be able to start studying artificial intelligence. - For reference, this lecture is not about "using AI in my work" or "getting started with monetization methods using GPT". - This is a video about how students, graduate students, or developers can get started when they want to study artificial intelligence.

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.