Practical Docker: Creating your own deep learning cloud computer with Docker

You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.

Packed with LLM Fine-Tuning Know-how, learned from Silicon Valley LLM Project Practitioners.

This course covers the process of automating algorithmic trading in local and cloud environments, and focuses on hands-on practice.

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

Packed with LLM Fine-Tuning Know-how, learned from Silicon Valley LLM Project Practitioners.

Instead of long and boring theories, you can learn them one by one through short practical exercises, and as you flesh them out one by one, you will soon be able to experience the overall architecture composition.

From the basics of machine learning & deep learning! Creating and utilizing classification/regression/clustering/artificial neural networks with Python

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.

Through this lecture, you can learn about understanding SQL and databases, SQL syntax, database design for practical application, database utilization through programming, and even data analysis application cases.

This course is for those who need to introduce data analysis, machine learning, AI, etc. to their work but are not familiar with Python programming. You will systematically learn the core functions of Python required to become a data scientist in a short period of time.

In this course, you will acquire basic knowledge about Azure virtual machines and learn how to design and manage virtual machines according to workload.

Now display Python results as web pages! You can create your own web page using only Python. This is an opportunity to create an Interactive Dashboard that allows you to check results created with Python, such as data analysis and machine learning, on a web page!

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

This is a course that intensively covers gradient descent, the most fundamental learning algorithm in deep learning.

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

This is a lecture on how to use NumPy and practice its application in real-world scenarios.

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

This is a lecture on creating and deploying your own GPT using various resources in Azure. From start to finish! Let's deploy a complete service from scratch!

Revolutionize your stock investments with AI! In this lecture, you will directly build a real, working AI automated trading system targeting the top 25 NASDAQ stocks. We provide a special opportunity to gain experience and know-how through simulated investments with the 한국투자증권 API, and to perform AI stock automated trading with a real account. Even stock beginners will have no problem. We will easily explain basic stock concepts and why you should invest in US stocks, and provide all source code and remote support. From now on, investment is essential for the next 60 years of our lives. Create your own AI investment partner that will be with you!

The Intermediate Python course is designed to deepen your understanding of Python by covering advanced topics such as functional programming, metaprogramming, exception handling, and object-oriented programming.

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

Learn NoSQL technology, which can handle Big Data, one of the fundamental technologies in full-stack and data science utilized by modern startups. MongoDB is the easiest and quickest technology to utilize among NoSQL databases. In this lecture, you will learn the basics of MongoDB in a short time, and also acquire the skills to manipulate and utilize MongoDB with Python.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

In application development, "being able to quickly and accurately reproduce the development environment" is extremely important. One effective means for achieving this is Docker. This video explains everything from Docker's basic concepts and ideas to the actual process of building and running applications using only Docker. You'll also learn the basics of docker-compose, which allows you to manage multiple containers together, giving you a better understanding of environment setup that's closer to real-world practice.