Python معالجة مسبقة للبيانات و تحليلها بواسطة from Coursera

فى نهاية هذا المشروع ، ستكون قادرًا على تحليل بيانات Quandl من خلال معالجة مسبقة للبيانات وهي عملية جمع البيانات واختيارها وتحويلها للإجابة على أسئلة باستخدام Python. في هذا المشروع ، ستتمكن من جمع البيانات لعام 2020 بأكملها والاستعلام عنها من موقع Quandl باستخدام واجهة برمجة التطبيقات الخاصة بها (API). إنه موقع مجاني للبيانات. ستتمكن من تحويل بيانات JSON التي تم إرجاعها إلى قاموس Python. وستكون قادرًا على تحليل هذه البيانات لحساب أعلى وأدنى الأسعار في هذه الفترة ، التغيير الأكبر بناءً على السعر المرتفع والمنخفض خلال هذا العام ، وأخيرًا متوسط التغير خلال هذا العام.

هذا المشروع مخصص للأشخاص في مجال الأعمال وتحليل البيانات. الأشخاص الذين يرغبون في مناقشة و معالجة البيانات وتوضيح حالة الاستخدام والتنبؤ بالعلاقات بين بيانات المصدر. و يوفر لك الخطوات المهمة لتكون محلل بيانات. علاوة على ذلك ، فإنه يزودك بالمعرفة في أساسيات Python فى البيانات.

What's inside

Syllabus

ملخص المشروع

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Tailored for professionals in business and data analysis who desire to refine their data wrangling, processing, and interpretation skills

Provides a solid foundation in Python data fundamentals

Empowers learners to analyze real-world data from Quandl using Python

Guides learners through interpreting JSON data, calculating key metrics, and extracting insights from financial data

Taught by Omnya Khaled, an experienced data scientist and instructor

Requires learners to have some prior knowledge of Python and data analysis concepts

Reviews summary

Course is great for learning data science

This course is highly recommended for learners who want to learn or enhance their knowledge in the field of data science and data analysis using Python.

Course content is good.

"..."

Course is recommended for beginners.

Course has learning objectives in data analysis and data processing.

"This project is specifically designed for people in business and data analysis to discuss and clean the data, explain the use case, and predict the relations between the source data"

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 Python معالجة مسبقة للبيانات و تحليلها بواسطة with these activities:

متابعة دروس تعليمية حول تحليل بيانات Quandl

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ستزودك هذه الدروس التوجيهية بمزيد من المعرفة والممارسة في تحليل بيانات Quandl.

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ابحث عن دروس تعليمية حول تحليل بيانات Quandl في منصات مثل Coursera أو Udemy
اختر درسًا تعليميًا يتناسب مع مستوى مهاراتك
اتبع الدروس التعليمية وأكمل التمارين

المشاركة في ورشة عمل حول تحليل بيانات Quandl

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ستوفر لك ورشة العمل هذه فرصة للتفاعل مع الخبراء في هذا المجال وتطبيق مهاراتك بشكل عملي.

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ابحث عن ورش عمل حول تحليل بيانات Quandl في منطقتك أو عبر الإنترنت
سجل في ورشة عمل تناسب أهدافك التعليمية
حضر ورشة العمل وشارك بنشاط في التدريبات

الانضمام إلى مجموعة دردشة جماعية لمناقشة تحليل بيانات Quandl

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ستتيح لك هذه المجموعة فرصة للتفاعل مع زملائك ومناقشة أفكارك حول تحليل بيانات Quandl.

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انضم إلى مجموعة دردشة جماعية على Slack أو Discord
شارك في المناقشات حول مواضيع تحليل بيانات Quandl
اطرح الأسئلة وشارك رؤيتك مع المجموعة

Three other activities

Expand to see all activities and additional details

Show all six activities

ممارسة الأسئلة التفاعلية

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سيساعدك هذا النشاط على تعزيز فهمك لمبادئ تحليل البيانات وممارسة تطبيقها على سيناريوهات واقعية.

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قم بزيارة الموقع الإلكتروني لـ Quandl واختر مجموعة بيانات مناسبة
اكتب كود Python لاستخراج البيانات من Quandl وتخزينها في DataFrame بانداس
حلل البيانات باستخدام Pandas للعثور على أعلى وأدنى الأسعار والتغييرات الكبرى
قم بتصور البيانات باستخدام Matplotlib أو Seaborn

إنشاء تقرير تحليلي

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سيساعدك هذا النشاط على تطبيق معرفتك بتحليل البيانات لحل مشكلة حقيقية وإعداد تقرير شامل.

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حدد سؤال بحثي حول تحليل البيانات
اجمع البيانات ذات الصلة من Quandl أو مصادر أخرى
حلل البيانات باستخدام تقنيات التحليل الاحصائي
اكتب تقريرًا موجزًا يوضح نتائجك واستنتاجاتك

إنشاء عرض توضيحي لتحليل بيانات Quandl

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سيسمح لك هذا النشاط بتلخيص وتطبيق معرفتك من خلال إنشاء محتوى تعليمي للآخرين.

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اختر موضوعًا لفيلمك التوضيحي
جمع المعلومات والبيانات من Quandl ومصادر أخرى
أنشئ عرضًا تقديميًا باستخدام PowerPoint أو Google Slides
سجل عرضك التقديمي وشاركه على YouTube أو Vimeo

Career center

Learners who complete Python معالجة مسبقة للبيانات و تحليلها بواسطة will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst gathers, analyzes, and interprets data to draw meaningful conclusions and identify trends. They play a vital role in making sense of complex information and communicating it effectively to decision-makers. This course can help build a foundation for a career as a Data Analyst by providing a solid understanding of data preprocessing, analysis techniques, and Python libraries commonly used in the field.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their expertise in statistics, machine learning, and programming to extract knowledge from data. They develop and implement analytical models to solve business problems and make predictions. This course can help aspiring Data Scientists gain a practical understanding of data preprocessing and analysis, which are essential skills for success in this role.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

Quantitative Analysts apply mathematical and statistical techniques to analyze financial data and assess risks. They play a critical role in the financial industry by providing insights for investment decisions and risk management. This course can provide a strong foundation for Quantitative Analysts by developing their skills in data preprocessing, analysis, and Python programming.

See salaries and explore the career path for Quantitative Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data analysis and visualization techniques to provide insights into business operations and performance. They help businesses make informed decisions by identifying trends, patterns, and opportunities. This course can be beneficial for Business Intelligence Analysts as it provides hands-on experience in data preprocessing, analysis, and Python libraries, which are essential for success in this role.

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Financial Analyst

Financial Analysts provide insights into financial markets and investments. They analyze financial data to make recommendations on investment decisions and risk management. This course can be a valuable resource for Financial Analysts as it provides a foundation in data preprocessing, analysis, and Python programming, which are essential skills for success in this field.

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Market Research Analyst

Market Research Analysts conduct research to understand consumer behavior and market trends. They use data analysis techniques to identify opportunities and develop strategies for businesses. This course can provide Market Research Analysts with a strong foundation in data preprocessing, analysis, and Python, which are essential skills for effective market research.

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Data Engineer

Data Engineers design, build, and maintain data pipelines to ensure the availability, reliability, and security of data. They play a critical role in managing and processing large datasets. This course can help aspiring Data Engineers develop their skills in data preprocessing, analysis, and Python, which are essential for success in this role.

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Software Engineer

Software Engineers design, develop, and maintain software systems. They use programming languages and software development tools to create applications that meet user needs. This course can be a valuable resource for Software Engineers as it provides a foundation in data preprocessing, analysis, and Python, which are increasingly important skills for modern software development.

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Statistician

Statisticians use statistical methods to collect, analyze, interpret, and present data. They work in various fields, including research, healthcare, and finance. This course can provide aspiring Statisticians with a solid foundation in data preprocessing, analysis, and Python programming, which are essential skills for success in this role.

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Epidemiologist

Epidemiologists investigate the causes and patterns of health and disease in populations. They use data analysis techniques to identify risk factors and develop strategies for disease prevention and control. This course can be beneficial for aspiring Epidemiologists as it provides a foundation in data preprocessing, analysis, and Python, which are increasingly important skills for modern epidemiology.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They work in various fields, including insurance, finance, and consulting. This course can provide aspiring Actuaries with a solid foundation in data preprocessing, analysis, and Python, which are increasingly important skills for modern actuarial practice.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. They develop and implement solutions to improve efficiency and productivity. This course can be beneficial for aspiring Operations Research Analysts as it provides a foundation in data preprocessing, analysis, and Python, which are valuable skills for this role.

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Risk Manager

Risk Managers identify, assess, and manage risks faced by organizations. They develop and implement strategies to mitigate risks and protect the organization's assets and reputation. This course can be a valuable resource for Risk Managers as it provides a foundation in data preprocessing, analysis, and Python, which are increasingly important skills for modern risk management.

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Compliance Officer

Compliance Officers ensure that organizations comply with laws, regulations, and ethical standards. They conduct risk assessments, develop compliance programs, and monitor adherence to policies and procedures. This course can be beneficial for aspiring Compliance Officers as it provides a foundation in data preprocessing, analysis, and Python, which are valuable skills for this role.

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Auditor

Auditors examine financial records and operations to ensure accuracy and compliance with laws and regulations. They play a critical role in ensuring the integrity of financial information and protecting against fraud and errors. This course may be useful for aspiring Auditors as it provides a foundation in data preprocessing, analysis, and Python, which are increasingly important skills for modern auditing.

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