Getting Started with MATLAB

Let's understand the main algorithms of machine learning and deep learning, and learn about artificial intelligence!

Let's develop basic field knowledge of clothing science and the capabilities of a fashion specialist through understanding AI-based textile CAD!

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

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

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

ChatGPT, become a creator using generative AI!

Understand and learn about Artificial Intelligence and AI ethics, and strengthen your AI digital capabilities by integrating them with your own field of study!

Modern C++ programming based on object-oriented concepts for computer science majors

Let's look into how to deploy Abyss for non-majors!

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

Let's experience collaborative application development in a Linux shell and open-source software environment, and set up the development environment required for coding!

Let's understand data analysis suitable for advanced retail business and learn how to utilize tools utilized in the industry!

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

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

Learn the fundamentals of website building and gain everything from web development basics to practical application skills through hands-on projects integrating public data Open APIs!

Let's understand and try policy evaluation with R and R Studio!

Let's manage projects efficiently and smartly through data science

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!

Are you a digital talent interested in coding and the Internet of Things (IoT)? Get started with programming through MicroPython!

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.

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

Covers essential linear algebra for Machine Learning/Deep Learning research.

- 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.

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.

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.