최신 빅데이터 및 인공지능 트렌드 이해

Do you want to take your first step into the world of data? Learn machine learning and deep learning, the core technologies of AI, with Python. This course will guide you step by step, from the basics of machine learning and deep learning to practical applications. Traditional machine learning and deep learning are based on many of the same principles and technical systems. Therefore, this course does not separate the two into separate subjects, but rather organizes them into one connected course so that beginners can increase their understanding of machine learning as a whole.

This course teaches you how to use generative AI models using the OpenAI API. In this course, you will learn the basics of using the API, how to use various language models, and practical programming examples and applications to learn how to apply generative AI in real life.

Natural Language Processing (NLP) is one of the fastest growing areas of artificial intelligence. This course covers a wide range of topics, from the basics of NLP to the latest NLP techniques using deep learning. In particular, it provides an in-depth understanding of cutting-edge generative models such as ChatGPT.

Are you new to coding or looking to take your coding skills to the next level? This course will introduce you to Python, a powerful and flexible language, designed for all levels of learners. Taught in a “follow-along” fashion, this course will allow you to learn by actually writing and running code. You’ll discover why Python is one of the most popular programming languages. From artificial intelligence to web development, learning the Python language offers endless possibilities, and it’s an opportunity to greatly expand your personal potential.

Understand the operating principles of generative AI models using deep learning and learn how to utilize them through practice.

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

You can acquire an overview of machine learning and deep learning, how to use basic tools, and the Python language knowledge necessary for learning in a short period of time.

This course covers everything from the basic concepts of recommendation systems to the principles of applying deep learning. Learn about various recommendation algorithms such as collaborative filtering, content-based filtering, and hybrid recommendation systems, and develop practical skills for developing recommendation services!

In the modern business world, data security and fraud prevention have become more important than ever. This lecture focuses on how to effectively detect and analyze fraudulent transactions using artificial intelligence (AI). Using Python and machine learning, we will build an AI model that can detect and detect anomalies in various industries, such as fraudulent transactions, credit card fraud, and production line abnormalities, early.

Financial data such as stocks, exchange rates, coins, real estate, and bonds are easily accessible and provide us with opportunities to make money, but most people miss valuable opportunities because they do not know their characteristics and how to handle them. Through this lecture, you can learn how to understand the meaning of various financial data and how to analyze them using Python.

All the recent amazing achievements in the field of artificial intelligence have been announced in the field of reinforcement learning. We have covered reinforcement learning technology, which is revolutionizing true artificial intelligence technology such as robots, autonomous driving technology, and human-like machines, from the basics to the advanced level, in an easy-to-understand way for beginners.

Learn how to build deep learning models directly through intuitive and Pythonic PyTorch. This reflects the latest PyTorch version.

JavaScript, which is known to all web developers, now explore the world of machine learning with this powerful language! This course learns how to build and deploy machine learning models using JavaScript and the powerful machine learning library Tensorflow.js. It guides you step-by-step through all the technologies required to develop web-based machine learning applications. Through this course, learners will systematically understand the core principles of machine learning. In addition, you will learn how to develop deep learning models using JavaScript and Tensorflow.js APIs, how to utilize transfer learning based on pre-trained models, and how to apply all this knowledge interactively in a browser environment.

An AI lecture without difficult terminology or difficult mathematical formulas! We help you understand AI theory through source code.

You can benchmark manufacturing innovation plans for semiconductors and run machine learning and deep learning on semiconductor data without coding.

The Certified Big Data Analyst exam is a nationally recognized certification administered twice a year. This course provides detailed lectures from the basics to the core concepts for those preparing for the exam. The difficulty of the exam increases with each iteration. To address this, we provide various important topics from the basics to improve the pass rate.

Ace the Big Data Analysis Engineer certification, a must-have credential that's far from easy to self-study, in a short amount of time by mastering the data analysis tool R, known for its ease of use!

If you want to be recognized as a machine learning expert based on large-scale data, from understanding the core framework of Spark machine learning, to SQL-based data processing through difficult practical problems, to data analysis through business domain analysis, and to the ability to implement optimized machine learning models, please join this course.

This is a lecture that provides a lot of practice on the basic grammar of Python. This is a lecture that provides practical practice used in machine learning and deep learning along with the grammar of Python.

[Python for AI] This is the second lecture in the series. It is a lecture that covers Python grammar along with practical exercises used in machine learning and deep learning.

Develop computational thinking and problem-solving skills using block coding entry, learn artificial intelligence concepts through entry AI tools, and practice simple machine learning.

The "Pytorch Projects Explained in One Code" edition implements practical deep learning projects using image, video, and natural language data. It focuses on code-centered learning rather than theory, to understand the structure and flow of models.

Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!

Still managing ML experiments manually? 🤔 Automate everything from experiment tracking to model deployment with MLflow and dramatically boost development productivity! A must-have skill for data scientists and ML engineers 💡 Start now! 🚀

Time series lecture to become a data analysis expert! Let's become an analyst strong in theory and practice!