파이썬의 데이터 과학 소개 from Coursera

What's inside

Syllabus

파이썬을 사용한 데이터 조작의 기초

이번 주에는 데이터 과학 분야를 소개하고, 데이터 과학자가 사용하는 일반적인 파이썬 기능 및 특징을 검토하고, 강의를 위해 Coursera Jupyter Notebook을 소개합니다. 채점, 전제 조건 및 기대치에 대한 모든 코스 정보는 강의 계획서에 있으며 과정 리소스 페이지에서 Jupyter Notebook에 대한 자세한 정보를 찾을 수 있습니다.

pandas를 사용한 기본 데이터 처리

이번 주 과정에서는 파이썬이 데이터 정리 및 처리를 위해 가지고 있는 가장 중요한 툴킷 중 하나인 pandas의 기초를 배우게 됩니다. DataFrame 구조로 데이터를 읽는 방법, 이러한 구조를 쿼리하는 방법, 이러한 구조에 대한 세부 정보가 인덱싱되는 방법을 배우게 됩니다.

pandas로 더 많은 데이터 처리

이번 주에는 DataFrame을 병합하고, 요약 테이블을 생성하고, 데이터를 논리적 조각으로 그룹화하고, 날짜를 조작하는 방법을 학습하여 python pandas 라이브러리에 대한 이해를 심화할 것입니다. 또한 데이터 규모에 대한 이해를 새롭게 하고 분석을 위한 메트릭 생성과 관련된 문제에 대해 논의합니다. 일주일은 더 중요한 프로그래밍 과제로 끝납니다.

지저분한 데이터로 질문에 답하기

이번 주 과정에서는 분포, 샘플링 및 t-검정과 같은 다양한 통계 기법을 소개합니다. 한 주가 과학에 대한 두 가지 토론과 네 번째 패러다임인 데이터 기반 발견의 부상으로 마무리됩니다.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

이 과정은 파이썬의 기초 개념부터 응용 분석까지 폭넓은 개념을 다룹니다

산업에서 널리 사용되는 람다, csv 파일, numpy 라이브러리의 기초를 소개합니다

파이썬에서 데이터를 조작하고 분석하기 위한 기본적인 프로그래밍 기술을 배울 수 있습니다

유명한 pandas 라이브러리를 사용하여 데이터를 정리하고 조작하는 데 능숙해집니다

인기 있는 함수인 groupby, merge, pivot table을 적극적으로 사용하는 방법을 연습할 기회가 제공됩니다

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in 파이썬의 데이터 과학 소개 with these activities:

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Career center

Learners who complete 파이썬의 데이터 과학 소개 will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist uses data to solve business problems. This course may be useful for Data Scientists who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Data Scientists who want to be able to work with large datasets and extract meaningful insights from them.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer builds and deploys machine learning models. This course may be useful for Machine Learning Engineers who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Machine Learning Engineers who want to be able to work with large datasets and extract meaningful insights from them.

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Business Analyst

A Business Analyst uses data to help organizations make better decisions. This course may be useful for Business Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Business Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Operations Research Analyst

An Operations Research Analyst uses mathematical and statistical models to solve business problems. This course may be useful for Operations Research Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Operations Research Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Statistician

A Statistician collects, analyzes, and interprets data. This course may be useful for Statisticians who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Statisticians who want to be able to work with large datasets and extract meaningful insights from them.

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Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course may be useful for Software Engineers who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Software Engineers who want to be able to work with large datasets and extract meaningful insights from them.

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Data Analyst

A Data Analyst collects, cleans, and analyzes data to help organizations make informed decisions. This course may be useful for Data Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Data Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Financial Analyst

A Financial Analyst evaluates and prices financial assets. This course may be useful for Financial Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Financial Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Risk Analyst

A Risk Analyst assesses and manages risk. This course may be useful for Risk Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Risk Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Data Engineer

A Data Engineer builds and maintains data pipelines. This course may be useful for Data Engineers who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Data Engineers who want to be able to work with large datasets and extract meaningful insights from them.

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Data Visualization Specialist

A Data Visualization Specialist creates visual representations of data. This course may be useful for Data Visualization Specialists who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Data Visualization Specialists who want to be able to work with large datasets and extract meaningful insights from them.

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Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical models to analyze financial data. This course may be useful for Quantitative Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Quantitative Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Market Researcher

A Market Researcher collects and analyzes data to understand market trends. This course may be useful for Market Researchers who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Market Researchers who want to be able to work with large datasets and extract meaningful insights from them.

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Insurance Analyst

An Insurance Analyst evaluates and prices insurance risks. This course may be useful for Insurance Analysts who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Insurance Analysts who want to be able to work with large datasets and extract meaningful insights from them.

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Data Journalist

A Data Journalist uses data to tell stories. This course may be useful for Data Journalists who want to learn how to use Python for data manipulation and analysis. The course covers topics such as data structures, data cleaning, data visualization, and statistical analysis. These skills are essential for Data Journalists who want to be able to work with large datasets and extract meaningful insights from them.

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