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Programming

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Programming Language

Big Data Analysis and Visualization Using Python

We explored the essential Python syntax necessary for big data analysis and, through various examples, presented methods such as big data file processing and visualization.

2 learners are taking this course

  • kpcre
데이터분석
빅데이터
파이썬
Python
Big Data

What you will learn!

  • Can understand the importance of data science and identify Python libraries necessary for data analysis.

  • Can learn Python functions for data analysis.

  • Pandas allows for data collection and analysis.

  • Data analyzed for decision-making can be visualized as charts and documented.

The beginning of data science, Python big data analysis and visualization!


Since the 4th industrial revolution, the importance of managing, analyzing, and utilizing big data has increased to the point where people say, "The next 100 years will be a battle of big data." The ability to collect accurate information in a short period of time and analyze it effectively is becoming an essential competency for office workers. In this course, we will look at the core Python grammar required for big data analysis and present methods for processing and visualizing big data files through various examples.

It is designed to help you understand the importance of data science, understand the Python libraries required for data analysis, and learn Python functions that can analyze data. It presents methods for collecting and analyzing data using Pandas, and it is designed to help you visualize and data-format the analyzed data into charts for decision-making.


Field-oriented education

  • We will learn Python functions that can analyze data, and present methods for collecting and analyzing data.

  • Based on real-world examples, we present methods for transforming complex information into visuals suitable for reporting.


Presenting key points centered on practice

  • Topic-based learning is possible through micro-learning centered on core keywords that can be immediately applied in practice.

Course Contents


  1. Understanding Data Science

  2. Configuring the development environment

  3. Understanding and practicing Numpy

  4. Understanding and practicing Pandas

  5. Practice Handling DataFrames

  6. Practice adding and selecting DataFrames

  7. Practice modifying and deleting DataFrame

  8. Data File Processing (1)

  9. Data file processing (2)

  10. Check data information

  11. Check statistical information

  12. Missing value conversion

  13. Delete missing values

  14. Data visualization for decision making

  15. Enhanced visualization library

  16. Titanic Exploratory Data Analysis


Differentiated content provided through the recruitment of instructors who have been verified in offline education

We have invited lecturers who are well-received for their in-depth lectures at companies, public institutions, and universities to present differentiated content.

CEO Park Sung-baek

Current) Code Campus CEO

Currently, Python Department Instructor at Korea Productivity Center

Former instructor at Ssangyong Education Center, SIS Co., Ltd.

Former Mobile Lab Information Education Center Instructor

Former) Instructor at Kyungshilyeon Hi-Tel Information Education Center


Recommended for
these people

Who is this course right for?

  • App Dev & DB Management New Practitioners

  • All office workers aiming to optimize their work with programming

  • All executives and employees who need practical application of big data analysis.

Hello
This is

338

Learners

26

Reviews

4.6

Rating

131

Courses

1987년에 설립된 한국생산성본부 부설기관으로, 기업과 공공기관의 임직원을 대상으로 회사생활에 꼭 필요한 직무교육을 제공하고 있습니다.

실제 기업의 업무에서 일어나는 ‘일’을 바탕으로 실무역량 강화를 위한 직무역량(Job-Duty-Task) 기반의 교육 콘텐츠를 구성했습니다.

차원이 다른 직무교육을 경험해 보세요!

홈페이지 : https://www.kpcice.or.kr

Curriculum

All

48 lectures ∙ (10hr 37min)

Published: 
Last updated: 

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$84.70

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