Are you still using pandas? Switch your data analysis stack to Polars+Streamlit right now

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

You can implement hands-on practice of infinitely generating cryptocurrency trading signals automatically using ChatGPT and Python, and backtesting and validating them. Additionally, you can learn how to combine all the strategies automatically generated by AI into a single strategy and apply it to actual trading.

The [Customized Basic Python for Data Analysis] course that even non-majors have easily completed! Learn the basics of using ChatGPT alongside it to create a "starting point" for data analysis and AI utilization. From essential prerequisites for data analysis to customized learning from a "Data Analysis Instructor," you can build deep foundational skills while learning quickly. This course instills the courage and confidence needed for coding and provides a roadmap for your future data analysis studies.

This course focuses on developing practical visualization skills that can be immediately applied in the workplace by utilizing Seaborn, a core tool for data visualization, and plotly/Dash for building interactive dashboards. Through various hands-on exercises, you can enhance both your ability to create insight-driven visual materials and implement web-based dashboards.

If you could draw graphs but couldn't explain the data, this course is a process for building the "ability to read and explain" data. In PART 3, we perform Exploratory Data Analysis (EDA) focusing on real-world cases. ✔ Checking data distribution ✔ Analyzing relationships between variables ✔ Outlier detection and visualization interpretation You will learn the analysis structure using the Titanic and Iris datasets, and through a project utilizing TMDB 5000 movie data, you will directly experience the entire analysis process: Data cleaning → Setting analysis topics → Visualization interpretation. By the end of this course, you will possess the analytical capability to read and explain data.

This is an introductory course on the Python programming language. Rather than a formal and tedious structure of simply printing text and following syntax, this course covers fundamental principles at an appropriate level regarding 'why' and 'how' things work, along with actual programming practice. Additionally, various course materials are provided.

Are you feeling anxious because it seems like everyone is trying Vibe Coding except you? Unsure of where to even begin? Don't worry. SSG Coach is here to help. Game development isn't difficult when you're Vibe Coding with AI. I will guide you so that anyone can create a game using only the free Gemini CLI. I will also provide essential game development knowledge, so that after completing this course, you'll be ready to take on other game projects as well.

A course to understand and practice machine learning for efficiently conducting complex analysis and predictions! Even machine learning, which may seem difficult and complex, can be easy and fun to master with Masocampus's <Python Machine Learning>.

Creating your own data analysis portfolio with Google Antigravity CLI harness engineering and vibe coding: data collection, analysis, reporting, dashboard creation, and task automation. Even if you are new to data collection, once you master the principles, prompt engineering, and how to use Antigravity, you can perform data collection, analysis, visualization, reporting, and dashboard creation just like a data analyst. From Python data collection to report writing learned with Antigravity IDE and CLI. Prompt writing and error resolution methods for foolproof data collection and analysis.

Learn from the beginning how to set up a development environment that even an ordinary office worker can easily understand. It is practice-oriented and focuses on students learning various development tools such as Vim, VS Code, Git, Docker, and remote development. You can learn how to build an efficient development environment by learning step-by-step from the basic usage of each development tool to advanced functions.

How to easily set up git, VS Code, Node.js, Python, Java dev environments on Windows within 2 hours without struggling.

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.

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

In this course, you will learn how to program kernels and develop PyTorch modules. You can use the knowledge you have gained to develop models faster.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

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.

I wanted to briefly cover the basics of Python through Jupyter Notebook, which allows you to immediately check the results of your coding.

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

Finally, the Probability and Statistics course for everyone is here! Learn the principles of probability and statistics step by step through theory and coding practice. Reference book "Probability and Statistics for Everyone" https://wikidocs.net/book/18165

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

We will learn how to develop Python, a general programming language that is widely used for data analysis, web development, security, and more, more efficiently.

* Lecture for those who are new to Git and GitHub * Basic Git features and Git-related plugins in VS Code