R البرمجة باستخدام لغة from Coursera

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Syllabus

الأسبوع الأول: الخلفية والشروع في العمل والإجراءات العملية

يتناول هذا الأسبوع الأساسيات للبدء مع لغة البرمجة R. ويحتوي درس مواد الخلفية على معلومات حول ميكانيكا الدورة التدريبية وبعض مقاطع الفيديو حول تثبيت R. كما تغطي مقاطع فيديو الأسبوع الأول تاريخ R وS، وتصفح أنواع البيانات الأساسية في R، ووصف دوال قراءة البيانات وكتابتها. أوصي بمشاهدة مقاطع الفيديو بالترتيب المدرج، ومشاهدة مقاطع الفيديو خارج الترتيب لن تُفسد القصة.

الأسبوع الثاني: البرمجة باستخدام R

مرحبا بك في الأسبوع الثاني من دورة البرمجة R. في هذا الأسبوع سوف نخلع القفازات وستغطي الدروس الموضوعات الأساسية مثل البنيات والدوال. كما سنقدم أول مهمة برمجة لهذه الدورة وموعد تسليمها نهاية الأسبوع.

الأسبوع الثالث: دوال حلقة التكرار وتصحيح الأخطاء

قد وصلنا الآن للأسبوع الثالث من برمجة R، والذي يمثل نقطة المنتصف. سوف تغطي دروس هذا الأسبوع دوال حلقة التكرار وأدوات تصحيح الأخطاء في لغة البرمجة R. وسوف تجعل هذه الجوانب R مفيدة في كلٍّ من العمل التفاعلي وكتابة الرموز الأطول وهي شائعة الاستخدام في مجال العمل.

الأسبوع الرابع: المحاكاة والتعريف

يتناول هذا الأسبوع كيفية محاكاة البيانات في R، والتي هي بمثابة أساس لإجراء دراسات المحاكاة. نحن نوفر أيضًا محلل ملفات التعريف في R والذي يتيح لك جمع معلومات مفصلة حول كيفية تشغيل دوال R الخاصة بك وتحديد الأزمات التي يمكن معالجتها. يعد محلل ملفات التعريف أداة رئيسية لمساعدتك في تحسين برامجك. وأخيرًا، نعرض دالة str، والتي أعتقد شخصيًا أنها الدالة الأكثر فائدة في R.

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Explores concepts and tools frequently applied in data science and other disciplines where data is analyzed

Taught by recognized experts in data analysis, Roger D. Peng, PhD, Jeff Leek, PhD, and Brian Caffo, PhD

Develops essential skills in data analysis for beginners and provides a strong foundation for intermediate learners

Uses R, a widely-used programming language in data analysis

Provides hands-on labs and interactive materials for practical application

Covers essential topics in data analysis, including programming in R, data wrangling, data visualization, and statistical modeling

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 البرمجة باستخدام لغة with these activities:

Solve Data Manipulation Problems

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Hone your data manipulation skills by practicing with real-world problems.

Browse courses on Data Manipulation

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Find a dataset online
Load the dataset into R
Practice cleaning and manipulating the data
Analyze the results

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Career center

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

Data Analyst

Data Analysts use programming languages like R to analyze data and extract insights from it. This course in Programming with R will help you build a foundation in R that will be useful for a career as a Data Analyst. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Data Analysts.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians use programming languages like R to analyze data and draw conclusions from it. This course in Programming with R will help you build a foundation in R that will be useful for a career as a Statistician. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Statisticians.

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Machine Learning Engineer

Machine Learning Engineers use programming languages like R to develop and deploy machine learning models. This course in Programming with R will help you build a foundation in R that will be useful for a career as a Machine Learning Engineer. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Machine Learning Engineers.

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Data Scientist

Data Scientists use programming languages like R to analyze data and extract insights from it. This course in Programming with R will help you build a foundation in R that will be useful for a career as a Data Scientist. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Data Scientists.

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Epidemiologist

Epidemiologists use programming languages like R to analyze data in the field of public health. This course in Programming with R will help you build a foundation in R that will be useful for a career as an Epidemiologist. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Epidemiologists.

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Biostatistician

Biostatisticians use programming languages like R to analyze data in the field of biology. This course in Programming with R will help you build a foundation in R that will be useful for a career as a Biostatistician. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Biostatisticians.

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Quantitative Analyst

Quantitative Analysts use programming languages like R to analyze data and make financial decisions. This course in Programming with R will help you build a foundation in R that will be useful for a career as a Quantitative Analyst. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Quantitative Analysts.

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Actuary

Actuaries use programming languages like R to analyze data in the field of insurance. This course in Programming with R will help you build a foundation in R that will be useful for a career as an Actuary. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all essential skills for Actuaries.

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Market Researcher

Market Researchers use programming languages like R to analyze data and make marketing decisions. This course in Programming with R may be useful for a career as a Market Researcher. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Market Researchers.

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Business Analyst

Business Analysts use programming languages like R to analyze data and make business decisions. This course in Programming with R may be useful for a career as a Business Analyst. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Business Analysts.

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Operations Research Analyst

Operations Research Analysts use programming languages like R to analyze data and make decisions about how to improve operations. This course in Programming with R may be useful for a career as an Operations Research Analyst. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Operations Research Analysts.

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Software Engineer

Software Engineers use programming languages like R to develop software. This course in Programming with R may be useful for a career as a Software Engineer. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Software Engineers.

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Financial Analyst

Financial Analysts use programming languages like R to analyze data and make financial decisions. This course in Programming with R may be useful for a career as a Financial Analyst. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Financial Analysts.

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Data Engineer

Data Engineers use programming languages like R to build and maintain data pipelines. This course in Programming with R may be useful for a career as a Data Engineer. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Data Engineers.

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Computer Scientist

Computer Scientists use programming languages like R to develop new algorithms and technologies. This course in Programming with R may be useful for a career as a Computer Scientist. The course covers topics such as data cleaning, data visualization, and statistical modeling, which are all skills that can be useful for Computer Scientists.

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