The easiest introduction to data analysis for non-majors

Everyone's dream blog! Create a differentiated blog that you can make and operate yourself, rather than a blog that you can see anywhere! Challenge yourself now with a Github blog!

Build and share your own data analysis app quickly and easily using Streamlit!

Pandas is one of the most widely used libraries in Python. Pandas, which has become an essential element for data analysis, you can learn everything about Pandas, the essential library for Python data analysis, through the <Pandas in One Shot> lecture.

This is a free lecture from TedNote's 'Note Series'. This lecture is intended for Python beginners. We provide a separate e-book textbook so that you can learn even if you follow the daunting Python study. You can find more lectures on the YouTube channel 'TedNote'.

This course covers data analysis using ChatGPT and Pandas utilization. Get a preview of the changed future ChatGPT will create.

Let's collect and refine data through public data, web scraping, etc. and analyze the data exploratively!

Let's build a foundation for using Python and solve data analysis problems!

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

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.

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.

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

Learn how to collect data from the web and create a supervised learning model for machine learning!

Learn network programming from scratch, fully utilizing Python and ChatGPT. Rather than tedious conceptual explanations, the focus is on students directly writing network code through practical exercises and personally verifying how their written programs operate. You can acquire skills ranging from basic network practicals to network technologies applicable in real-world scenarios, and build deep understanding and proficiency through exercises dealing with various protocols and tools. Furthermore, by leveraging ChatGPT, students can have a memorable learning experience without feeling difficulty or boredom.

This course provides a complete introduction to programming with Python. You will start from the very basics and gradually build up to writing more advanced scripts and solving real-world coding challenges. With step-by-step explanations, practical exercises, and projects, this course is perfect for anyone looking to start their coding journey or strengthen their foundation in Python.

AI does the coding, I get the results! Maximize practical programming skills, achievable even for beginners!

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.

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.

Building Your Own Data Analysis Portfolio with GEMINI CLI Vibe Coding - No Payment Required Data Collection, Analysis, Reports, Dashboard Creation, and 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 just like a data analyst. Learning Python from Data Collection to Analysis Report Writing with GEMINI CLI and VSCode Prompt Writing and Error Resolution Methods for Foolproof Data Collection and Analysis

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'?

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

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

QML is a programming interpreter language for creating UIs provided by Qt. It is similar to JSON and can use JavaScript. Using QML and Python together, you can easily develop modern, advanced UIs.

A Complete End-to-End Developer Journey — Build Lightning-Fast APIs, Modern Frontend Interfaces, Real Projects, Authentication Systems, Dashboards & Full Deployments Using FastAPI, React, and Vibe Coding Techniques.

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.