Python & xử lý dữ liệu dễ dàng bắt đầu cùng HeartCount

This is a replay of the eleventh webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your work.

This is a replay video of the 10th webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your work.

This is a replay video of the ninth webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your work.

I'll teach you how to use Excel effectively in your work and how to create data that's good for analysis.

Learn how to effectively use GA4 in your business.

This is a replay of our eighth webinar on how to use the free, no-coding data visualization tool, 'HEARTCOUNT'. Instead of spending time learning about data or learning tools, spend it finding the insights you need from your data.

This is a replay of our seventh webinar on how to use the free, no-coding data visualization tool, 'HEARTCOUNT'. Instead of spending time learning data or learning tools, spend it finding the insights you need from your data.

This is a replay of our sixth webinar on how to use the free, no-coding data visualization tool, 'HEARTCOUNT'. Instead of spending time learning data or learning tools, spend it finding the information you need from your data.

We cover machine learning algorithms, especially regression analysis and decision trees, that are used to identify patterns in data and make predictions. You will understand what regression analysis and decision trees are and how they are used.

This is a replay of our fifth webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your business.

This is a replay of our fourth webinar on how to use the free data visualization tool 'HEARTCOUNT' that requires no coding. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your business.

This is a replay of our third webinar on how to use the free, no-coding data visualization tool, 'HEARTCOUNT'. Instead of spending time learning data or learning tools, spend it finding the information you need from your data for your business.

This is a replay of our second webinar on how to use the free, no-coding data visualization tool, 'HEARTCOUNT'. Don't spend too much time learning data or learning tools, use that time to find the insights you need from your data for your work.

Here's a replay of our first webinar on how to use the free, no-coding data visualization tool, 'HEARTCOUNT'. Don't spend too much time learning data or learning tools, use that time to find the information you need in your data for your business.

We cover the data literacy required to become an organization/individual that handles data well, as well as the basic theory of data visualization. Build a solid foundation to utilize data “well.”

This is a lecture on data visualization using the Matplotlib library.

🚀 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.

You can learn the skills and know-how needed to improve work efficiency by utilizing Open API and Python.

You can use Python to analyze large amounts of data and visualize the analyzed data in graph form so that you can easily understand it at a glance.

This course is for both beginners who have never been exposed to programming before and those who have some theoretical knowledge about Python. The main purpose of the course is to create interest and enjoyment in Python based on real projects. I hope that through this course, you will gain more ideas and have more fun with Python.

A course to understand and practice machine learning that efficiently performs complex analysis and prediction! Machine learning, which seemed difficult and complicated, can be easily and enjoyably learned in its core with Maso Campus' <Python Machine Learning>.

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.

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.

This is a basic course on Python Excel programming that you can learn with the xlsxwriter tutorial. You can analyze data and automate tasks using Python and Excel.

This course aims to acquire Python-based web crawling technology to collect data from web pages and improve data collection and analysis capabilities at work based on this.

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

I will guide non-majors and beginners to quickly pass the Big Data Analysis Engineer practical exam! Theory lightly, practice thoroughly. Even without complex background knowledge, focusing on past questions, we intensively study only the points sure to appear on the exam.

AI that thinks and adapts? Now you can build it yourself. Master the core of reinforcement learning with intuitive explanations and code, not complex theories, and grow into a 'practical developer' through finance and industry projects.

This lecture is a follow-up lecture to 'Python Data-Based Stock Quant Investment Part 1'. If Part 1 was more of an introduction, Part 2 is an in-depth lecture that focuses on the entire flow of practical strategy implementation and quantitative investment development. This class focuses on advanced Pandas techniques for handling time series data, and how to implement signal-based strategies and static/dynamic asset allocation strategies that require adjusting asset weights at various intervals based on this. Furthermore, it goes beyond strategy implementation and learns about 'code framework' that directly verifies and backtests various investment strategies with minimal code modifications, how to extend this to improve it so that it can lead to actual investment, and what to watch out for in this process. In addition to the programming component, you can experience the best Python quant investment flow that you cannot find in investment books, blogs, YouTube, etc. by deeply covering theoretical contents such as the two types of return concepts (simple return, log return) and evaluation indicators related to backtesting.

Building Your Own Data Analysis Portfolio with Free GEMINI CLI Vibe Coding Data Collection, Analysis, Reports, and Dashboard Creation for Work Automation Even if you're new to data collection, by learning the principles, prompt writing methods, and VSCode usage, you can perform data collection, analysis, visualization, reports, and dashboard creation like a data analyst. From Python Data Collection to Analysis Report Writing with GEMINI CLI and VSCode Prompt Writing and Error Resolution Methods for Foolproof Data Collection and Analysis

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

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

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!

If you're just learning Python and don't know what you can do or what you should do? Let's learn how to use web technologies with Python, such as web crawling, automation, and APIs.

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.