Data Analysis Learned Through Python Code

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!

Basic manners, etiquette, and communication skills training to foster global leaders leading the era of the Fourth Industrial Revolution.

Let's collect and refine data through public data, web scraping, and more, and perform exploratory data analysis!

Let's use the R language, which processes data easily and conveniently, to help even non-computer science majors develop their skills in utilizing computer programs related to their own fields!

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

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

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

Let's become creators using ChatGPT and generative AI!

Java Programming Based on Object-Oriented Concepts for Computer Science Majors

Let's practice learning how to translate real-life and major-related problems into actual computer programs and utilizing Python-based AI tools!

Let's develop the capability to extract useful information from large-scale data and support decision-making!

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

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

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

Learn machine learning techniques using Python and improve your ability to extract information from real-world data and develop predictive models!

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

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

Are you a digital talent interested in the Internet of Things (IoT)? Let's get started with IoT through Arduino!

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!

From the basics of Numpy and Pandas to data preprocessing, visualization, and crawling, all in one place! This is an introductory Python course for data analysis.

Learn about the basics of Python required for data analysis, the data analysis framework (pandas), and the data analysis process.

Data analysis sounds a bit grandiose, but it is actually a process of establishing a hypothesis and verifying it based on data. You can learn how to analyze what data to verify your hypothesis using Python.

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.

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

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

In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.

In this class, you will learn about the principles and methods of analyzing and processing various types of financial data using Python's Pandas library, apply them to situations you may encounter in the real world, and ultimately learn how to implement backtesting based on financial statement data (based on Kang Hwan-guk's book, "You Can Do Quant Investment"). As a result, you can break away from being a "passive investor" who simply follows what others say without verifying or basing the investment logic, and become a "self-directed and active investor" who can freely extract various elements necessary for strategy implementation from data and quantitatively analyze them using Python and Pandas.

1. A practice-oriented lecture designed to help you pass the AICE Associate, Korea's only nationally recognized AI certification. 2. Learn to the level of performing data analysis and AI modeling based on Python.

Let's use the R language, which processes data easily and conveniently, to help even non-computer science majors develop their skills in utilizing computer programs related to their own fields!

Master the Big Data Analysis Certification—an essential credential that is by no means easy to self-study—in a short period using R, an easy-to-learn data analysis tool!

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

We will develop a web app that collects data using concurrent/parallel programming in Python, loads it into MongoDB, analyzes it, and visualizes the collected data using FastAPI, a modern web framework. In the process, you will learn and understand Python concurrent/parallel programming using coroutines, multi-threading, and multi-processing, and understand how to use them to improve Python's performance. We will help you apply Python concurrent/parallel codes directly to your work. We will not only teach you how to develop and end, but also how to deploy and operate an actual app on the AWS cloud.

You will thoroughly understand the principles!

Learn how to process big data from a Silicon Valley software engineer & how to develop big data code with Apache Spark using Python. I am a 14-year software developer who handles everything from web applications to big data and SRE & DevOps with Python. Don't miss this opportunity to learn about Apache Spark, which is essential for big data professionals, in an easy and in-depth way using Python!

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

This lecture is designed for job seekers preparing for Evaluation and Analysis roles in Samsung Electronics' DS Division (Memory, S.LSI, Foundry, TSP, AVP) and PE, AE, and Solution PE roles at SK hynix, who are struggling with the differences between business units and job functions. You will learn how to categorize job titles by company based on the actual workflow of Product Evaluation roles and how to translate your major-related experiences into professional terminology suitable for resumes and interviews. We will help you establish an application strategy by connecting experiences in Analog circuit design, Verilog/FPGA, process experiments, and data analysis with key industry terms such as Yield, Wafer Map, Shmoo Plot, and Failure Analysis.

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

Have you been getting stuck on linear algebra formulas every time you try to study AI? Instead of memorizing formulas, this lecture shows you visually how vectors and matrices actually move in space. By the end of the course, you will be able to interpret the mathematics behind neural networks, PCA, and SVD on your own.

"Why does my automated trading collapse in a bear market?" I have also deeply pondered this same question. Most automated trading logics on the market seem to generate profits during a bull market, but they lose their ability to respond the moment the market sentiment changes. To solve this problem, I have combined the know-how I researched myself over the past two years with the latest AI technology. In this course, you will learn how to directly design a 'Transformer-based deep learning model' that simultaneously reads macroeconomic trends and individual stock flows, and how to automatically train and deploy it in a free GPU environment. In particular, we will introduce sophisticated data normalization techniques at the hedge fund level to build an 'Intelligent Comprehensive Scoring System' that goes beyond simple indicators to incorporate news sentiment. To this, we add an 'AI Safety Gate' that implants the insight of a trader with 20 years of experience on Wall Street, adding a final layer of confidence from a human trader's perspective right before a purchase. Beyond simple buying and selling functions, you will directly implement the entire process of an institutional-grade algorithmic system by adding dynamic take-profit and stop-loss logic, eight self-recovery mechanisms, and real-time Slack reports.