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Data Science

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Data Analysis

Data analysis starting with Python (from Python grammar for data analysis to data collection, preprocessing, and exploration)

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.

(4.6) 7 reviews

50 learners

  • ilifo
파이썬입문
이론 실습 모두
Python
Numpy
Pandas
Seaborn
Matplotlib

What you will learn!

  • Basic concepts of Python such as variables, data types, conditional statements, loops, functions, modules, and packages

  • How to process large amounts of data quickly and efficiently based on an understanding of Numpy and Pandas

  • Data visualization using Seaborn and Matplotlib

  • How to create a program that receives an HTML document from a server and extracts only the desired results

  • Writing a program that dynamically operates the browser

Data analytics is no longer a fad; it's essential knowledge .

Those of you who have clicked on this lecture have likely encountered situations where you needed to analyze data yourself, or perhaps felt pressured (or perhaps even pressured?) by others to learn data analysis. And I'm confident that everyone will experience this in the future, though the timing may vary. Data analysis provides essential information for understanding the world and making critical decisions.

Data analysis, once considered the domain of a select few specialists just a few years ago, has now become a widely recognized, universally applicable skill, practically a required liberal arts subject. We live in an era where anyone should be able to perform data analysis.

Features of this course

📌 This is a basic Python programming course for exploratory data analysis .

📌 We focus on core functions frequently used in data analysis .

📌 This practical Python course will teach you the fundamentals of exploratory data analysis through various practical examples .

📌 Data that can be used in real life, such as Samsung Electronics stock price data and National Health Insurance Corporation health checkup information data I have constructed an example using data .

I recommend this to these people

Introduction to Python, what's next?
I took the introductory course
I'm trying to use it in real life
Where and how to start
People who have a lot of problems in one way or another

I'm interested in data analysis.
From Python basic grammar
Learning step by step
Data analysis technology
Those who want to acquire

I want to try collecting data myself.
Crawling HTML on the web
Collect the data you want directly
Anyone who wants to use it for analysis

After class

  • Numerical calculations on large amounts of data become possible.

  • You can now graph the movement of Company A's stock price over the past five years.

  • You can see in a graph whether there is a correlation between temperature and sales.

  • You can collect price information from multiple shopping malls and save it in Excel.

  • You can create a program that automatically downloads photos of your favorite idols.

Learn about these things.

Basic concepts of Python

Learn the basic concepts of Python, including variables, data types, conditional statements, loops, functions, modules, and packages.

Numpy, Pandas

Learn how to process large amounts of data quickly and efficiently.

Data visualization using Seaborn and Matplotlib

Learn how to visualize your data in a way that suits its characteristics.

Web Crawling

Learn how to retrieve an HTML document from a server and extract only the desired results from the HTML.

If you have laid the foundation for analysis with [Data Analysis with Python],

[Machine Learning + Deep Learning with Python] to utilize AI!

Why Python?

Although Python and R are widely used in data analysis, it's not always easy to understand the differences between them. Therefore, many people struggle to decide which language to choose before even beginning data analysis. While there's no right answer, as both Python and R are excellent programming languages for data analysis, if your goals for data analysis are as follows, I recommend choosing Python.

  1. I want to work as an IT engineer
    Programs written in Python offer the advantage of being easily ported to existing IT systems. There are a variety of IT systems in the world, including portal sites, shopping malls, and financial transaction systems. Programs written in Python are ideal for adding to existing IT systems.

  2. I want to learn deep learning based on artificial neural networks.
    Most of the recently popular deep learning algorithms are written in Python. Therefore, if you want to ultimately learn machine learning and deep learning algorithms, as well as statistical data analysis, I recommend starting your data analysis with Python.

  3. I want to learn a widely used programming language.


    Python is the third most widely used programming language worldwide, following C and Java. Furthermore, the number of Python users is steadily increasing, and the advantage of a widely used language is that it offers a wealth of information. The algorithms I need are often already available as packages, and with the constant stream of high-performance algorithms being developed and shared, I can avoid the hassle of implementing every single part of my program myself.

Things to note before taking the course

Practice environment

  • The training will be conducted using Jupiter Notebook in Anaconda.

  • For data collection and crawling, the results of the exercise may vary depending on whether the site being practiced changes.

Recommended for
these people

Who is this course right for?

  • For those who are new to Python for data analysis

  • For those who dream of becoming a data analyst

Hello
This is

261

Learners

12

Reviews

2

Answers

4.3

Rating

3

Courses

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인스타그램: https://www.instagram.com/ilifo0182/

유튜브: https://www.youtube.com/channel/UCYqYscK7l_1Z5AT1Of0KUkQ

Curriculum

All

29 lectures ∙ (6hr 40min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

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7 reviews

4.6

7 reviews

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