Python بُنى بيانات from Coursera

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Syllabus

الفصل السادس: السلاسل

في هذا الفصل الدراسي، سنتابع من حيث توقفنا في الفصل الدراسي السابق، بدءًا من الفصل 6 من الكتاب النصي لنغطي السلاسل النصية وننتقل إلى بُنى البيانات. ويُخصص الأسبوع الثاني من هذا الفصل الدراسي لتثبيت Python، إذا كنتم تريدون بالفعل تشغيل التطبيقات على كمبيوتر سطح مكتب أو جهاز الكمبيوتر المحمول الخاص بكم. إذا اخترتم تثبيت Python، فيمكنكم تخطي الأسبوع الثالث والتقدم في الدورة.

الوحدة: تثبيت Python واستخدامه

في هذه الوحدة سوف تقومون بإعداد الأشياء حتى تتمكنون من كتابة برامج Python. ونحن لا نطلب تثبيت Python لهذا الفصل الدراسي. ويمكنكم كتابة واختبار برامج Python في المتصفح باستخدام "Python Code Playground" في هذا الدرس. يُرجى قراءة مادة "استخدام Python في هذا الفصل الدراسي" للاطلاع على التفاصيل.

الفصل السابع: الملفات

حتى الآن، كنا نعمل باستخدام البيانات التي تتم قراءتها من المستخدم أو البيانات في الثوابت. لكن البرامج الفعلية تعالج كميات كبيرة للغاية من البيانات عن طريق قراءة وكتابة الملفات في تخزين ثانوي على جهاز الكمبيوتر الخاص بكم. وفي هذا الفصل نبدأ في كتابة برامجنا الأولى التي تقرأ وتفحص وتعالج البيانات الحقيقية.

الفصل الثامن: القوائم

نظرًا لأننا نريد حل المشكلات الأكثر تعقيدًا في Python، فنحن بحاجة إلى متغيرات أكثر قوة. حتى الآن، كنا نستخدم متغيرات بسيطة لتخزين الأرقام أو السلاسل حيث يكون لدينا قيمة واحدة في أي متغير. وبدءًا من القوائم، سنُخزِّنُ العديد من القيم في متغير واحد باستخدام مخطط فهرسة لتخزين قيم مختلفة من داخل متغير واحد وتنظيمها واستردادها. ونحن نطلق على هذه المتغيرات متعددة القيم اسم "المجموعات" أو "بُنى البيانات".

الفصل التاسع: القواميس

يُعد قاموس Python أحد أقوى بُنى البيانات. فبدلًا من تمثيل القيم في إحدى القوائم الخطية، تُخزِّنُ القواميس البيانات في صورة أزواج أساسية / أزواج قيم. يمنحنا استخدام الأزواج الأساسية / أزواج القيم "قاعدة بيانات" في الذاكرة في متغير Python واحد.

الفصل العاشر: المجموعات

المجموعات هي بنية بيانات Python الأساسية الثالثة والأخيرة التي سنتناولها. المجموعات هي إصدار بسيط من القوائم. وغالبًا ما نستخدم المجموعات جنبًا إلى جنب مع القواميس لإنجاز مهام متعددة الخطوات مثل الفرز أو التكرار خلال جميع البيانات في أحد القواميس.

التخرُّج

للاحتفال بوصولكم إلى نقطة منتصف الطريق في تخصص «Python للجميع»، فإننا نرحب بكم لحضور حفل تخرُّجنا عبر الإنترنت. وهو حفل ليس طويلًا للغاية، ويتميز بمتحدث في حفل التخرج وخطاب قصير جدًا عن حفل التخرج.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Geared towards learners already familiar with Python programming

Covers Python 3, which is current and widely used

Provides a solid foundation in Python data structures, building on learners' existing Python knowledge

Includes interactive materials and a course playground for hands-on practice

Part of a larger 'Python for Everybody' specialization, offering a comprehensive study of Python

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 بُنى بيانات with these activities:

استعادة مهارة كتابة الكود في Python

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سيساعدك ذلك على استعادة مهاراتك في كتابة الكود بـ Python والتي ستحتاجها طوال فترة الدورة التدريبية.

Browse courses on Python

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قم بزيارة موقع Python الرسمي وقراءة وثائق حول أساسيات لغة البرمجة.
حل المشكلات البسيطة كتمرين مثل العثور على الحد الأدنى أو الأقصى لقائمة الأرقام.

قراءة كتاب Python Crash Course، الإصدار الثاني بقلم إريك ماتيس

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سيساعدك مراجعة هذا الكتاب على تحديث معرفتك بأساسيات بايثون، وتوطيد مفاهيم السلاسل والملفات والقوائم والقواميس والمجموعات في بايثون.

Browse courses on Python

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شراء الكتاب أو استعارته من المكتبة أو تنزيله
تخصيص من 60 إلى 90 دقيقة يوميًا لقراءة الكتاب
قراءة الفصلين 6 و 7 وتدوين الملاحظات حول المفاهيم الرئيسية

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Career center

Learners who complete Python بُنى بيانات will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use their knowledge of statistics, programming, and machine learning to extract insights from data. This course provides a strong foundation in Python, which is a popular programming language for data science. The course covers topics such as data structures, algorithms, and machine learning, which are all essential skills for Data Scientists. Taking this course will help you develop the skills you need to succeed in this field.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. This course provides a solid foundation in Python, which is a popular programming language for machine learning. The course covers topics such as data structures, algorithms, and machine learning, which are all essential skills for Machine Learning Engineers. Taking this course will help you develop the skills you need to succeed in this field.

See salaries and explore the career path for Machine Learning Engineer

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 Python, which is a popular programming language for data analysis. The course covers topics such as data structures, algorithms, and data visualization, which are all essential skills for Data Analysts. Taking this course will help you develop the skills you need to succeed in this field.

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Software Engineer

Software Engineers design, develop, and maintain software applications. This course provides a solid foundation in Python, which is a popular programming language for software development. The course covers topics such as data structures, algorithms, and object-oriented programming, which are all essential skills for Software Engineers. Taking this course will help you develop the skills you need to succeed in this field.

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Data Engineer

Data Engineers are responsible for building and maintaining the infrastructure that supports data analysis and machine learning. This course provides a solid foundation in Python, which is a popular programming language for data engineering. The course covers topics such as data structures, algorithms, and cloud computing, which are all essential skills for Data Engineers. Taking this course will help you develop the skills you need to succeed in this field.

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Web Developer

Web Developers design, develop, and maintain websites. This course provides a solid foundation in Python, which is a popular programming language for web development. The course covers topics such as data structures, algorithms, and web programming, which are all essential skills for Web Developers. Taking this course will help you develop the skills you need to succeed in this field.

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Data Visualization Specialist

Data Visualization Specialists use visual representations to communicate data and insights. This course provides a solid foundation in Python, which is a popular programming language for data visualization. The course covers topics such as data structures, algorithms, and data visualization, which are all essential skills for Data Visualization Specialists. Taking this course will help you develop the skills you need to succeed in this field.

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Statistician

Statisticians collect, analyze, and interpret data. This course provides a solid foundation in Python, which is a popular programming language for statistics. The course covers topics such as data structures, algorithms, and probability, which are all essential skills for Statisticians. Taking this course will help you develop the skills you need to succeed in this field.

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Business Analyst

Business Analysts help businesses understand their data and make better decisions. This course provides a solid foundation in Python, which is a popular programming language for business analysis. The course covers topics such as data structures, algorithms, and data visualization, which are all essential skills for Business Analysts. Taking this course will help you develop the skills you need to succeed in this field.

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Data Journalist

Data Journalists use data to tell stories and inform the public. This course provides a solid foundation in Python, which is a popular programming language for data journalism. The course covers topics such as data structures, algorithms, and data visualization, which are all essential skills for Data Journalists. Taking this course will help you develop the skills you need to succeed in this field.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course provides a solid foundation in Python, which is a popular programming language for operations research. The course covers topics such as data structures, algorithms, and optimization, which are all essential skills for Operations Research Analysts. Taking this course will help you develop the skills you need to succeed in this field.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course provides a solid foundation in Python, which is a popular programming language for actuarial science. The course covers topics such as data structures, algorithms, and probability, which are all essential skills for Actuaries. Taking this course will help you develop the skills you need to succeed in this field.

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Financial Analyst

Financial Analysts help businesses make investment decisions. This course provides a solid foundation in Python, which is a popular programming language for financial analysis. The course covers topics such as data structures, algorithms, and financial modeling, which are all essential skills for Financial Analysts. Taking this course will help you develop the skills you need to succeed in this field.

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Risk Analyst

Risk Analysts help businesses identify and manage risks. This course provides a solid foundation in Python, which is a popular programming language for risk analysis. The course covers topics such as data structures, algorithms, and probability, which are all essential skills for Risk Analysts. Taking this course will help you develop the skills you need to succeed in this field.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data. This course provides a solid foundation in Python, which is a popular programming language for quantitative analysis. The course covers topics such as data structures, algorithms, and financial modeling, which are all essential skills for Quantitative Analysts. Taking this course will help you develop the skills you need to succeed in this field.

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