Let's get off work 5 minutes early! Python data analysis, visualization, and web dashboard creation

A course chosen by 3,000 students! Updated to GPT-5 version! How far can you go with ChatGPT? Create automated stock trading applications and web investment reports!

ChatGPT: How Far? Series, Stock auto-trading app & web inv. report creation!

No more encyclopedic lectures that cover everything! A Python introductory lecture that gathers only the key points for easy listening!

Here are some key competencies that are often overlooked by others in the fiercely competitive and complex semiconductor process job market.

No more lectures that start with boring grammar! Python practical application examples that jump straight into use

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 is a lecture on data visualization using the Matplotlib library.

This course is designed for beginners, students, and those who want to use Polars, aiming to acquire the necessary skills for data analysis, from basic concepts of the Python-based data analysis library Polars to simple data processing and exploratory data analysis (EDA).

In this course, you can learn a wide range of topics, from basic Excel functions to advanced formulas, data visualization, and dashboard creation, with a focus on hands-on practice. By providing templates and solution files, self-study is possible, and you can maximize work efficiency by mastering data analysis skills that can be immediately applied in real-world scenarios.

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

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.

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.

Hello! Have you ever gotten tired of repeatedly writing the same code over and over again while doing data analysis? 😫 Now let's give your projects wings with PyCaret! 🚀 This course will teach you the secret to automating most of the tedious and complex machine learning processes with just 5 lines of code. Here's how this course will transform you! ✨ Master Real-World Projects: 📈Customer purchase prediction (classification), 📉Medical cost prediction (regression), 🧩Customer grouping (clustering), ⏳Airline passenger prediction (time series)! You can develop 'real' problem-solving skills by following along with 4 core projects hands-on. Acquire Expert Skills: But that's not all! 🤖 We'll also teach you expert skills like managing your models with MLOps and creating API servers with just a few clicks. Pretty amazing, right? Protect Your Work-Life Balance: Most importantly, we'll drastically reduce your repetitive tasks and help you focus only on core analysis. Leaving work on time is a bonus! 😉 Whether you're not yet comfortable with coding or you're a current professional wanting to explosively boost productivity, everyone is welcome! 👋 Shall we transform together into a '10x faster data scientist'?

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>.

We explored the essential Python syntax necessary for big data analysis and, through various examples, presented methods such as big data file processing and visualization.

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

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

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.

🚀 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 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.

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

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 lecture is for beginners who are new to coding, as well as those who want to try out various uses of Python, covering basic concepts of Python, Numpy, Pandas, Plotly, Django, and crawling, as well as simple data 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.

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.