R 프로그래밍 from Coursera

What's inside

Syllabus

1주차: 배경, 시작하기, 너트와 볼트

이번 주에는 R을 시작하는 데 필요한 기본 사항을 다룹니다. 배경 자료 강의에는 과정 역학에 대한 정보와 R 설치에 대한 일부 비디오가 포함되어 있습니다. 1주차 비디오에서는 R 및 S의 역사를 다루고 R의 기본 데이터 유형을 살펴보고, 데이터를 읽고 쓰는 기능을 설명합니다. 나열된 순서대로 비디오를 시청하는 것이 좋지만 순서대로 시청하지 않아도 스토리라인이 끊기지는 않습니다.

2주차: R을 사용한 프로그래밍

R 프로그래밍 2주차에 오신 것을 환영합니다. 이번 주에는 강의에서 제어 구조 및 기능과 같은 주요 주제를 본격적으로 다룹니다. 또한 이번 주에 마감되는 이 과정의 첫 번째 프로그래밍 과제도 소개합니다.

3주차: 루프 함수 및 디버깅

이제 중간 지점이기도 한 R 프로그래밍의 세 번째 주에 들어섰습니다. 이번 주 강의에서는 R의 루프 기능과 디버깅 도구에 대해 설명합니다. R의 이러한 측면은 R을 대화식 작업과 더 긴 코드 작성 모두에 유용하게 만들므로 실제로 일반적으로 사용됩니다.

4주차: 시뮬레이션 및 프로파일링

이번 주에는 시뮬레이션 연구를 수행하기 위한 기초 역할을 하는 R에서 데이터를 시뮬레이션하는 방법을 다룹니다. 또한 R 기능이 실행되는 방식에 대한 자세한 정보를 수집하고 해결할 수 있는 병목 현상을 식별할 수 있는 R의 프로파일러를 다룹니다. 프로파일러는 프로그램을 최적화하는 데 도움이 되는 핵심 도구입니다. 마지막으로, 개인적으로 R에서 가장 유용한 함수라고 생각하는 str 함수를 다룹니다.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

학문적인 배경에 따라 통계적 컴퓨팅의 필요한 주제를 탐구합니다

교수 Jeff Leek, 박사는 통계학 및 전산학 분야의 저명한 학자입니다

현실적인 사례 연구를 통해 통계 데이터 분석을 탐구합니다

R 프로그래밍, 데이터 읽기, R 패키지 액세스, 디버깅, 프로파일링 등 통계 컴퓨팅의 실질적인 문제를 다룹니다

초보자를 위한 R 프로그래밍 기초를 제공하는 첫 주 강의를 포함합니다

실습 과제를 통해 학습 과정을 보강하는 프로그래밍 과제가 있습니다

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 R 프로그래밍 with these activities:

연습문제 풀기

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R 프로그래밍 기본 사항 연습을 통해 숙련도 향상.

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제공된 연습문제 수집
문제 풀기
답안 확인 및 개선 사항 파악

간단한 R 프로젝트 시작하기

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실제 프로젝트를 수행하여 R 프로그래밍 기술 적용 및 심화.

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작은 규모의 실습 프로젝트 계획
데이터 수집 및 준비
R을 사용하여 데이터 분석 및 시각화
프로젝트 결과 보고서 작성

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Career center

Learners who complete R 프로그래밍 will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data scientists use data to solve complex problems and make informed decisions. This course provides a strong foundation in R programming, which is a powerful tool for data analysis and visualization. By learning how to use R, you will be able to effectively analyze data, identify trends, and communicate your findings to stakeholders. Additionally, this course covers topics such as data wrangling, statistical modeling, and machine learning, which are all essential skills for data scientists.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. This course provides a strong foundation in R programming, which is a widely used statistical software package. By learning how to use R, you will be able to perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as probability, inference, and regression analysis, which are all essential skills for statisticians.

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Data Engineer

Data engineers design and build data pipelines to collect, store, and process data. This course provides a solid foundation in R programming, which is a popular language for data engineering. By learning how to use R, you will be able to build and maintain data pipelines, perform data transformations, and ensure data quality. Additionally, this course covers topics such as data warehousing, big data, and cloud computing, which are all essential skills for data engineers.

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Machine Learning Engineer

Machine learning engineers design and develop machine learning models to solve real-world problems. This course provides a solid foundation in R programming, which is a popular language for machine learning. By learning how to use R, you will be able to build and train machine learning models, evaluate their performance, and deploy them into production. Additionally, this course covers topics such as supervised learning, unsupervised learning, and deep learning, which are all essential skills for machine learning engineers.

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Data Analyst

Data analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a solid foundation in R programming, which is a powerful tool for data analysis and visualization. By learning how to use R, you will be able to effectively analyze data, identify trends, and communicate your findings to stakeholders. Additionally, this course covers topics such as data wrangling, statistical modeling, and machine learning, which are all essential skills for data analysts.

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Public Health Analyst

Public health analysts use data to improve the health of populations. This course provides a solid foundation in R programming, which is a popular language for statistical computing and data analysis. By learning how to use R, you will be able to perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as epidemiology, biostatistics, and public health, which are all essential skills for public health analysts.

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Financial Analyst

Financial analysts use financial data to make investment recommendations. This course provides a solid foundation in R programming, which is a popular language for financial modeling and data analysis. By learning how to use R, you will be able to build and test financial models, analyze financial data, and communicate your findings effectively. Additionally, this course covers topics such as financial statement analysis, valuation, and risk management, which are all essential skills for financial analysts.

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Operations Research Analyst

Operations research analysts use mathematical and statistical methods to solve problems in the field of operations management. This course provides a solid foundation in R programming, which is a widely used statistical software package in the field of operations research. By learning how to use R, you will be able to perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as linear programming, network optimization, and simulation, which are all essential skills for operations research analysts.

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Quantitative Analyst

Quantitative analysts use mathematical and statistical methods to analyze financial data and make investment decisions. This course provides a solid foundation in R programming, which is a popular language for quantitative analysis. By learning how to use R, you will be able to build and train financial models, evaluate their performance, and make informed investment decisions. Additionally, this course covers topics such as time series analysis, risk management, and portfolio optimization, which are all essential skills for quantitative analysts.

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Actuary

Actuaries use mathematical and statistical methods to assess risk and uncertainty. This course provides a solid foundation in R programming, which is a widely used statistical software package in the insurance industry. By learning how to use R, you will be able to perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as risk management, insurance pricing, and financial modeling, which are all essential skills for actuaries.

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Epidemiologist

Epidemiologists investigate the causes and distribution of disease. This course provides a solid foundation in R programming, which is a popular language for statistical computing and data analysis. By learning how to use R, you will be able to perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as biostatistics, epidemiology, and public health, which are all essential skills for epidemiologists.

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Economist

Economists use economic theory and data to analyze economic issues and make policy recommendations. This course provides a solid foundation in R programming, which is a popular language for economic modeling and data analysis. By learning how to use R, you will be able to build and test economic models, analyze economic data, and communicate your findings effectively. Additionally, this course covers topics such as econometrics, macroeconomics, and microeconomics, which are all essential skills for economists.

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Biostatistician

Biostatisticians apply statistical methods to solve problems in the field of biology. This course provides a solid foundation in R programming, which is a widely used statistical software package in the biological sciences. By learning how to use R, you will be able to perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as bioinformatics, genomics, and epidemiology, which are all essential skills for biostatisticians.

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Market Researcher

Market researchers use data to understand consumer behavior and trends. This course provides a solid foundation in R programming, which is a popular language for market research and data analysis. By learning how to use R, you will be able to collect and analyze market data, identify trends, and communicate your findings effectively. Additionally, this course covers topics such as survey design, data analysis, and market segmentation, which are all essential skills for market researchers.

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Software Engineer

Software engineers design, develop, and maintain software applications. This course provides a solid foundation in R programming, which is a popular language for statistical computing and data analysis. By learning how to use R, you will be able to develop software applications that can perform complex statistical analyses, create visualizations, and communicate your findings effectively. Additionally, this course covers topics such as object-oriented programming, software design, and testing, which are all essential skills for software engineers.

See salaries and explore the career path for Software Engineer