인프런 - 라이프타임 커리어 플랫폼

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

There was a rumor that Ediya would open a store near Starbucks. How different would the locations of Ediya and Starbucks be? Will the real estate price fluctuation trend from 2013 to 2019 be reflected in the apartment sales price? What kind of parks are there in my neighborhood? How can I utilize the data in the public data portal? The goal is to become familiar with Python and various data analysis libraries by handling various types of data through public data.

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

How to Read the World with Data: Explore Your Own Data Science! Dive deep and practically into the tools and techniques that form the core of modern data science. In particular, you will learn how to analyze data and implement algorithms using Anaconda, Numpy, Pandas, and Scikit-learn, essential components of data science.

This is not an investment lecture. It covers data collection, analysis, and visualization using stock market data. You will work with various data formats and learn various text preprocessing techniques. It covers visualization techniques for time-series data, methods for representing scales, and several techniques for interpreting stock price data. This course is about learning how to gain insights through data analysis. It is structured so that the concepts learned through stock price data can be applied to collecting, analyzing, and visualizing other time-series data such as demand, inventory, sales, and traffic volume.

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>.

From basics to advanced data analysis! Based on what you've learned, analyze data yourself using data from Jeju Island!

Let's understand data analysis methods using Python, analyze and visualize various types of data on our own, and organize an outline of our data story!

* 100% Practical Curriculum: Focused on hands-on data handling rather than grammar-based learning * Essential Machine Learning Prep: A complete summary of data preprocessing techniques required before AI training * Data Analysis Tool Mastery: Conquer core functions of Numpy (numerical operations) and Pandas (data manipulation) * Deriving Visualization Insights: Transferring data visualization skills using Matplotlib and Seaborn * Building Statistical Foundations: Learning basic statistics and group analysis techniques to identify data characteristics

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.

A process to upgrade from a beginner in Python to a Python practitioner! Learn about data analysis and data visualization using Python, and increase your ability to use it for company work through real-world projects.

This course is for those who need to introduce data analysis, machine learning, AI, etc. to their work but are not familiar with Python programming. You will systematically learn the core functions of Python required to become a data scientist in a short period of time.

We will cover the major Python libraries that you must learn to become a data analysis expert.

Learn about Python NumPy, a representative library in the field of data science. Learn NumPy and lay the foundation for learning data science!

From the basics of Numpy and Pandas to data preprocessing, visualization, and crawling, all in one place! This is an introductory Python course for data analysis.

Numpy and Pandas are the foundation of data analysis and the backbone of AI frameworks, and I've packed this course with the core practical know-how I've accumulated through my work and teaching experience. I've designed it with a hands-on approach so that marketers, planners, and beginner analysts can easily follow along with data cleaning and processing—the areas where they most often get stuck. Through this course, anyone can develop the skills to handle data and produce analysis results on their own, without needing help from developers.