تحليل البيانات الاستكشافية from Coursera

What's inside

Syllabus

الأسبوع الأول

يغطي هذا الأسبوع أساسيات الرسومات التحليلية ونظام الرسم الأساسي في R. وقد قمنا أيضًا بتضمين بعض المواد الأساسية لمساعدتك في تثبيت R إذا لم تكن قد قمت بذلك بالفعل.

الأسبوع الثاني

مرحبًا بكم في الأسبوع الثاني من تحليل البيانات الاستكشافية. يغطي هذا الأسبوع بعض أنظمة الرسومات البيانية الأكثر تقدمًا المتوفرة في R: نظام Lattice ونظام ggplot2. بينما يوفر نظام الرسومات base العديد من الأدوات المهمة لتصور البيانات، فقد كان جزءًا من نظام R الأصلي ويفتقر إلى العديد من الميزات التي قد تكون مرغوبة في نظام الرسم، خاصة عند تصور البيانات عالية الأبعاد. يعمل نظاما Lattice وggplot2 أيضًا على تبسيط تخطيط الرسومات مما يجعلها عملية أقل تعقيدًا.

الأسبوع الثالث

مرحبًا بكم في الأسبوع 3 من تحليل البيانات الاستكشافية. يغطي هذا الأسبوع بعض الأساليب الإحصائية المستخدمة في التحليل الاستكشافي. تتضمن هذه الأساليب تقنيات التجميع وتقليل الأبعاد التي تسمح لك بعمل عروض رسومية لبيانات ذات أبعاد عالية جدًا (العديد من المتغيرات). نغطي أيضًا طرقًا جديدة لتحديد الألوان في R بحيث يمكنك استخدام اللون كبُعد مهم ومفيد عند عمل رسومات البيانات. تمت تغطية كل هذه المواد في الفصول 9-12 من كتابي تحليل البيانات الاستكشافية مع R.

الأسبوع الرابع

في هذا الأسبوع، سنلقي نظرة على دراستي حالة في تحليل البيانات الاستكشافية. الأول يتضمن استخدام تقنيات التحليل العنقودي، والثاني هو تحليل أكثر تعقيدًا لبعض بيانات تلوث الهواء. غالبًا ما تكون طريقة عمل EDA أمرًا شخصيًا، لكني أقدم مقاطع الفيديو هذه لإعطائك فكرة عن كيفية المضي قدمًا في نوع معين من مجموعة البيانات.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

يقدم الأساسيات الأساسية لـ R والمرئيات وتقنيات تحليل البيانات الاستكشافية

يقوم بتدريسك كيفية تطبيق تقنيات التحليل الاستكشافي قبل البدء في النمذجة الرسمية

يغطي كيفية استخدام المخططات السفلية ونظام ggplot2 الأكثر تقدمًا

يوضح الأساليب الإحصائية متعددة المتغيرات المستخدمة لتصور البيانات عالية الأبعاد

يستخدم دراسات الحالة لإعطاء أمثلة عملية حول كيفية إجراء تحليل البيانات الاستكشافية

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 تحليل البيانات الاستكشافية with these activities:

أنشئ مجموعة شاملة لموارد الدورة التدريبية

Show steps

سيساعدك تجميع ملاحظاتك ومهامك واختباراتك في مكان واحد على البقاء منظمًا وإعدادك للدورة التدريبية بفعالية.

Show steps

جمع الملاحظات من المحاضرات
تنظيم المهام والاختبارات حسب الأسبوع
إنشاء مجلد رقمي للمواد

استكشف نظام الرسم البياني ggplot2

Show steps

سيوفر لك هذا الدرس العملي توجيهات خطوة بخطوة حول كيفية استخدام ggplot2 لإنشاء رسومات بيانات فعالة، مما يعزز مهاراتك في تحويل البيانات إلى رؤى.

Browse courses on Ggplot2

Show steps

تثبيت حزمة ggplot2
استيراد مجموعة بيانات إلى R
إنشاء رسم بياني أساسي باستخدام ggplot2
تخصيص المخططات باستخدام الخيارات الجمالية
حفظ المخططات بتنسيقات مختلفة

Show all two activities

Career center

Learners who complete تحليل البيانات الاستكشافية will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use data to solve business problems. They may work with Data Analysts to gather and clean data, and to develop machine learning models. This course may be useful for Data Scientists who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Data Scientists to identify trends and patterns in data, and to communicate their findings to stakeholders.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts use data to identify and solve business problems. They may work with Data Analysts and Data Scientists to gather and clean data, and to develop machine learning models. This course may be useful for Business Analysts who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Business Analysts to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Operations Research Analyst

Operations Research Analysts use data to improve the efficiency of businesses and organizations. This course may be useful for Operations Research Analysts who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Operations Research Analysts to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Statistician

Statisticians collect, analyze, and interpret data to provide insights to businesses and organizations. This course may be useful for Statisticians who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Statisticians to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Software Engineer

Software Engineers design and build software applications. This course may be useful for Software Engineers who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Software Engineers to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Data Analyst

Data Analysts gather, clean, and interpret data to provide insights to businesses. They may also work with data scientists to develop machine learning models. This course may be useful for Data Analysts who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Data Analysts to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Financial Analyst

Financial Analysts use data to make investment recommendations. This course may be useful for Financial Analysts who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Financial Analysts to identify trends and patterns in financial data, and to communicate their findings to stakeholders.

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Risk Analyst

Risk Analysts use data to identify and assess risks to businesses and organizations. This course may be useful for Risk Analysts who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Risk Analysts to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Data Engineer

Data Engineers design and build data pipelines that collect, clean, and store data. This course may be useful for Data Engineers who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Data Engineers to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Data Visualization Specialist

Data Visualization Specialists design and create visualizations that communicate data insights. This course may be useful for Data Visualization Specialists who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Data Visualization Specialists to identify trends and patterns in data, and to create visualizations that are clear and easy to understand.

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Quantitative Analyst

Quantitative Analysts use data to make investment recommendations. This course may be useful for Quantitative Analysts who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Quantitative Analysts to identify trends and patterns in financial data, and to communicate their findings to stakeholders.

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Actuary

Actuaries use data to assess and manage risk. This course may be useful for Actuaries who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Actuaries to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Epidemiologist

Epidemiologists use data to investigate the causes and spread of disease. This course may be useful for Epidemiologists who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Epidemiologists to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Biostatistician

Biostatisticians use data to design and analyze clinical trials. This course may be useful for Biostatisticians who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Biostatisticians to identify trends and patterns in data, and to communicate their findings to stakeholders.

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Market Researcher

Market Researchers collect and analyze data to understand consumer behavior. This course may be useful for Market Researchers who want to learn more about exploratory data analysis techniques. The course covers topics such as data visualization, data summarization, and statistical modeling. These skills can help Market Researchers to identify trends and patterns in consumer behavior, and to communicate their findings to stakeholders.

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