[Renewed] Python Data Analysis for Beginners (Easy! Learn the entire process of preprocessing, pandas, and visualization) [Data Analysis/Science Part1]

For those who want to learn data science, big data, and web crawling, (1) we summarize the most essential Python syntax in a short time, and (2) you'll become familiar with Python and crawling through practical crawling programming.

This is a newly designed course that allows you to gradually learn the mathematics, theory, PyTorch-based implementation, transfer learning, and GPT's core transformer needed to understand deep learning, based on the instructor's own failed experiences when first learning deep learning.

This course is Part 3 of the Full Stack lecture series, designed to help you solidly master the latest server technologies and Docker. The course is structured to enable you to practically incorporate Docker into your tech stack by meticulously testing Docker's various options, learning related technologies such as Linux that are necessary for understanding Docker, and building actual complex services.

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems

Learn intermediate to advanced SQL and solve 101 real-world data analysis problems together to build solid SQL data analysis skills.

This is a course where you can learn FastAPI, which is easy and fast for modern full-stack and backend development, starting from backend concepts step by step to FastAPI core syntax and asynchronous database usage, organized with clean materials and projects.

Based on real-world experience developing web services in the field, this is a full-stack series course aimed at helping beginners develop web and app services at a level suitable for actual commercialization. As the first step (part1-1) toward this goal, this course provides detailed explanations of intermediate Python, backend implementation techniques using Flask, and essential web technologies (HTTP, REST API, MVC pattern, etc.) for full-scale development.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.

This is a full-stack series course aimed at developing web and app services at a commercially viable level for beginners, based on real-world experience developing web services in the field. As Part 2 of this series, this course thoroughly covers the latest HTML5, CSS3, and vanilla JavaScript + ES6, considering responsiveness and compatibility among the various frontend technologies available.

This is Part 1 of a roadmap lecture that concisely organizes the essential computer science (CS knowledge) needed to excel in development and data, in a short period. This lecture has also been used as an in-house lecture at top domestic companies for several years. Based on 20 years of experience in actual practice, from system SW to web, app development, and data science, this lecture systematically yet easily organizes the essential core knowledge needed to excel in development and data.

This course is a comprehensive lecture where you can learn Flutter step by step, from the basics of dart programming to basic and intermediate Flutter features, even integrating with Firebase backend, all the way to actual projects!

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

Learn how to work efficiently using Python, a basic programming language.

This is a lecture on how to use NumPy and practice its application in real-world scenarios.

Through this course, you can learn SQL and database fundamentals, SQL syntax, database design for practical applications, database utilization through programming, and data analysis use cases.

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems

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

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.

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.

Learn NoSQL technology for handling big data, one of the fundamental skills in full-stack and data science technologies used by modern startups. MongoDB is the easiest and fastest NoSQL technology to utilize. In this course, you will learn the basics of MongoDB in a short time and master the skills to handle and utilize MongoDB with Python.

With Python Quant Investment, you can create investment strategies based on data and invest according to the strategy. You can implement various asset allocation strategies and ultimately create your own investment strategy.

Now display Python results as web pages! You can create your own web page using only Python. This is an opportunity to create an Interactive Dashboard that allows you to check results created with Python, such as data analysis and machine learning, on a web page!

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.

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.

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

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

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!

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.

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.

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.

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>.

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'?