도시정비법 및 건축법·주택법 해설
한국사회능력개발원
부동산개발 사업의 기본이 되는 부동산공법의 기본 흐름과 어려운 용어들을 정리하여 개발사업의 든든한 기초가 될 수 있도록 구성하였습니다.
입문
재테크
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.
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.
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.
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.
Topic-based learning is possible through micro-learning centered on core keywords that can be immediately applied in practice.
Understanding Data Science
Configuring the development environment
Understanding and practicing Numpy
Understanding and practicing Pandas
Practice Handling DataFrames
Practice adding and selecting DataFrames
Practice modifying and deleting DataFrame
Data File Processing (1)
Data file processing (2)
Check data information
Check statistical information
Missing value conversion
Delete missing values
Data visualization for decision making
Enhanced visualization library
Titanic Exploratory Data Analysis
We have invited lecturers who are well-received for their in-depth lectures at companies, public institutions, and universities to present differentiated content.
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
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.
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
All
48 lectures ∙ (10hr 37min)
13. Data Selection
16:22
14. Add new column
06:15
15. Data Aggregation
20:28
16. Add column
11:59
17. Add row
10:43
18. Select Element
36:47
$84.70
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