تحليل البيانات باستخدام بايثون from Coursera

تعرف على كيفية تحليل البيانات باستخدام بايثون. تنتقل بك هذه الدورة بدءًا من أساسيات بايثون إلى استكشاف العديد من أنواع البيانات المختلفة. سوف تتعرف على كيفية إعداد البيانات للتحليل وإجراء تحليل إحصائي بسيط وإنشاء مؤثرات عرض بيانات ذات مغزى والتنبؤ بالاتجاهات المستقبلية التي يتم استنتاجها من البيانات، وغير ذلك المزيد! الموضوعات المتناولة: 1) استيراد مجموعات البيانات 2) تنظيف البيانات 3) معالجة أُطر البيانات 4) تلخيص البيانات 5) تصميم نماذج انحدار التعلم الآلي 6) تصميم مسارات البيانات سوف يتم عرض وتقديم تحليل البيانات باستخدام بايثون عبر عدة وسائل تشمل: المحاضرة والتمرين المعملي والمهام. وتتضمن الدورة الأجزاء التالية: مكتبات تحليل البيانات: ستتعلم كيفية استخدام مكتبة بانداس ومكتبة نامبي ومكتبة سي باي للتعامل مع عينة من مجموعة البيانات. سنقدم لك مكتبة بانداس، وهي مكتبة مفتوحة المصدر سنستعين بها في تحميل مجموعات بيانات جاذبة للاهتمام ومعالجتها وتحليلها وعرض مؤثراتها. ثم سنقدم لك مكتبة أخرى مفتوحة المصدر، ألا وهي ساي كيت ليرن، وسنستخدم بعض خوارزميات التعلم الآلي الخاصة بها لتصميم نماذج ذكية وإبداء تنبؤات رائعة. إذا اخترت المشاركة في هذه الدورة والحصول على شهادة دورة Coursera، فستحصل أيضًا على شارة رقمية من شركة IBM. عرض لوقت محدود: تكلفة الاشتراك 39 دولارًا أمريكيًا فقط للشهر الواحد لتتمكن من الحصول على المواد المصنفة والشهادة.

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Taught by Joseph Santarcangelo, an established data science expert

Covers Python libraries essential for data analysis: Pandas, Numpy, and SciPy

Develops foundational data analysis skills, such as data cleaning, manipulation, and statistical analysis

Introduces machine learning concepts and empowers learners to create predictive models using Scikit-Learn

Aligned with industry practices and incorporates hands-on exercises for practical learning

Reviews summary

Utilitarian data analytics

This course titled, "تحليل البيانات باستخدام بايثون" teaches students how to work with data using Python including topics such as data cleaning, dataframe manipulation, and machine learning. There is currently limited data to determine the overall quality of this course, but one review indicates students can expect to learn how to use real-world Python libraries with a focus on data analysis and machine learning. No more reviews are available to determine the success rate of this course or how students generally feel about the course content.

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 باستخدام بايثون with these activities:

Read Python Crash Course, 2nd Edition

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Get a solid foundation in Python by reading a comprehensive and practical beginner's guide.

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Read chapters 1-5 to understand the basics of Python syntax and data types.
Complete the exercises at the end of each chapter to practice your skills.
Create a small Python project to apply what you've learned.

Follow Codecademy's Python Course

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Supplement your learning with interactive exercises and demonstrations from Codecademy.

Browse courses on Python

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Create an account on Codecademy.
Enroll in the Python course.
Complete the lessons and exercises in order.

Join a Python Study Group

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Engage with fellow learners, discuss concepts, and work through problems together.

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Find a study group or create your own.
Meet regularly to discuss course material and work on projects.

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Build a Simple Data Analysis App

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Solidify your understanding of Python's data analysis capabilities by building a practical application.

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Choose a dataset to work with and define the problem you want to solve.
Write Python code to load, clean, and analyze the data.
Use Pandas and Matplotlib to create visualizations that illustrate your findings.
Write a report or presentation to showcase your results.

Attend a Python Workshop

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Gain hands-on experience and learn from experts by attending a Python workshop.

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Find a relevant workshop in your area or online.
Register for the workshop and attend the sessions.

Create a Python Tutorial Video

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Enhance your understanding by explaining Python concepts to others through a video tutorial.

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Choose a specific Python topic to cover.
Create an outline and write a script for your video.
Record and edit your video using a screen recording software.
Upload your video to a platform like YouTube or Vimeo.

Design an Interactive Data Visualization

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Showcase your understanding of data visualization by creating an interactive dashboard or report.

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Choose a dataset and identify the key insights you want to convey.
Use Python libraries such as Plotly or Dash to create visualizations.
Deploy your visualization online or share it with others.

Career center

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

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to provide insights and drive decision-making. The course 'Data Analysis with Python' provides a comprehensive foundation in data analysis techniques using the popular Python programming language. Learners will develop skills in data manipulation, statistical analysis, and data visualization, which are essential for Data Analysts.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists are highly skilled professionals who use data to solve complex business problems. They possess expertise in machine learning, statistics, and computer science. The course 'Data Analysis with Python' offers a solid foundation in data analysis and machine learning principles. Learners will gain hands-on experience with real-world datasets, preparing them for entry-level Data Scientist roles.

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Statistician

Statisticians collect and analyze data to provide insights into various fields such as healthcare, finance, and marketing. The course 'Data Analysis with Python' covers statistical concepts and methods, including data summarization, hypothesis testing, and regression analysis. These skills are highly valuable for aspiring Statisticians seeking to build a strong foundation in data analysis.

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Market Researcher

Market Researchers conduct surveys, gather data, and analyze market trends to provide insights for businesses. The course 'Data Analysis with Python' equips learners with data analysis and visualization skills, enabling them to effectively analyze market data, identify patterns, and make data-driven recommendations.

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Business Analyst

Business Analysts bridge the gap between business stakeholders and IT teams, analyzing data to improve business processes and drive decision-making. The course 'Data Analysis with Python' provides a hands-on introduction to data analysis techniques, helping aspiring Business Analysts develop the skills needed to interpret data and provide valuable insights.

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Data Engineer

Data Engineers are responsible for designing, building, and maintaining data infrastructure. The course 'Data Analysis with Python' may be helpful for aspiring Data Engineers who seek to gain foundational knowledge in data manipulation and analysis. However, additional coursework and experience in data engineering principles and tools would be required to fully prepare for this role.

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Financial Analyst

Financial Analysts evaluate financial data to make investment recommendations. The course 'Data Analysis with Python' provides an overview of data analysis techniques, including statistical analysis and data visualization. While it may not directly prepare learners for all aspects of financial analysis, it can supplement their understanding of data-driven decision-making in the financial sector.

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Software Engineer

Software Engineers design, develop, and maintain software applications. While the course 'Data Analysis with Python' primarily focuses on data analysis techniques, it can be a valuable addition for aspiring Software Engineers seeking to enhance their data handling and analysis skills. Understanding data structures and algorithms is also essential for Software Engineers, which may require further coursework or self-study.

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Product Manager

Product Managers are responsible for defining and managing the development of products or services. The course 'Data Analysis with Python' provides insights into data analysis and visualization techniques, which can be beneficial for Product Managers who need to understand user data, market trends, and customer feedback to make informed decisions.

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Consultant

Consultants provide expert advice and guidance to organizations on various business issues. The course 'Data Analysis with Python' can be a valuable addition for aspiring Consultants who seek to enhance their analytical and problem-solving skills. Data analysis is becoming increasingly important in various industries, and Consultants with strong data analysis capabilities can provide valuable insights to their clients.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products or services. The course 'Data Analysis with Python' provides an introduction to data analysis and visualization techniques, which can be useful for Marketing Managers who need to analyze market data, track campaign performance, and measure customer engagement. However, additional coursework or experience in marketing principles would be required for a comprehensive understanding of the field.

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Operations Manager

Operations Managers oversee the day-to-day operations of businesses and organizations. The course 'Data Analysis with Python' may be helpful for aspiring Operations Managers who seek to enhance their data analysis and problem-solving skills. Data analysis can provide valuable insights into operational efficiency, resource allocation, and customer satisfaction.

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Project Manager

Project Managers plan, execute, and control projects to achieve specific goals. The course 'Data Analysis with Python' provides an overview of data analysis techniques, which can be beneficial for Project Managers who need to track project progress, identify risks, and make informed decisions based on data.

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Actuary

Actuaries use mathematical and statistical methods to assess risk and uncertainty in various fields such as insurance, finance, and healthcare. The course 'Data Analysis with Python' provides a foundation in data analysis and statistical modeling, which can be a valuable starting point for aspiring Actuaries. However, additional coursework and specialized training in actuarial science would be required to fully prepare for this role.

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UX Researcher

UX Researchers conduct research to improve the user experience of products and services. The course 'Data Analysis with Python' provides an introduction to data analysis and visualization techniques, which can be useful for UX Researchers who need to analyze user behavior, identify pain points, and make data-driven recommendations for design improvements.

See salaries and explore the career path for UX Researcher