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Alex Aklson
"الصورة تساوي ألف كلمة". كلنا يعرف هذا التعبير. إنه ينطبق بشكل خاص عند محاولة شرح نتائج التحليلات التي تم الحصول عليها من تحليل مجموعات البيانات الكبيرة المتزايدة. تؤدي مؤثرات عرض البيانات دورًا أساسيًا في تمثيل البيانات الصغيرة والكبيرة على حد سواء. ...
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"الصورة تساوي ألف كلمة". كلنا يعرف هذا التعبير. إنه ينطبق بشكل خاص عند محاولة شرح نتائج التحليلات التي تم الحصول عليها من تحليل مجموعات البيانات الكبيرة المتزايدة. تؤدي مؤثرات عرض البيانات دورًا أساسيًا في تمثيل البيانات الصغيرة والكبيرة على حد سواء. وتتمثل إحدى المهارات الأساسية لعالِم البيانات في قدرته على سرد قصة مقنعة، تعرِض البيانات والنتائج مصحوبة بمؤثرات عرض بطريقة ودّيّة ومحفِّزة. إن تعلم كيفية الاستفادة من أداة برمجية لمؤثرات عرض البيانات في صورة مؤثرات عرض سيمكنك أيضًا من استخراج المعلومات وفهم البيانات بشكل أفضل، واتخاذ قرارات أكثر فاعلية. والهدف الرئيسي من هذه الدورة التدريبية لمؤثرات عرض البيانات باستخدام لغة بايثون هو تعليمك كيفية أخذ البيانات التي تبدو لأول وهلة عديمة المعنى وتقديم تلك البيانات في شكل منطقي للجمهور. تم تطوير تقنيات مختلفة لعرض البيانات بشكل مرئي ولكن في هذه الدورة التدريبية، سنستخدم العديد من مكتبات مؤثرات عرض البيانات في لغة بايثون، وهي مكتبة مات بلوت ليب ومكتبة سيبورن ومكتبة فوليوم. عرض لفترة محدودة: سعر الاشتراك 39 دولارًا أمريكيًا فقط شهريًا للحصول على المواد المتدرّجة والشهادة.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides knowledge and skills that are applicable for roles in data analytics
Designed using a modular approach, allowing learners to choose their preferred learning modules
Led by expert instructors who are recognized for their knowledge and practical experience in data visualization
Utilizes a variety of Python libraries, including Matplotlib, Seaborn, and Volume, which are widely used in the data visualization field
Suitable for learners with beginner to intermediate experience in data science or data analytics
Course materials and resources are accessible for a reasonable subscription fee

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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 مؤثرات عرض البيانات باستخدام لغة بايثون with these activities:
Read 'Data Visualization: A Practical Introduction' by Kieran Healy
Expand knowledge of data visualization techniques and best practices by reading a foundational text in the field.
Show steps
  • Read Chapters 1-4 to understand the principles and history of data visualization.
  • Complete exercises and assignments to apply concepts and skills.
Compile resources on best practices in data visualization
Gather and organize valuable resources to enhance understanding of best practices in data visualization, facilitating reference and application.
Browse courses on Data Visualization
Show steps
  • Research and identify authoritative sources on data visualization best practices.
  • Collect and curate articles, books, tutorials, and other relevant resources.
  • Organize resources into categories or themes for easy navigation.
Review and practice Python coding basics
Refresh basic Python concepts by practicing coding drills to strengthen comprehension.
Show steps
  • Complete at least 20 coding exercises on a platform like LeetCode or HackerRank.
  • Review solutions and debug code to identify and correct errors.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow tutorials on advanced Python data manipulation techniques
Enhance data manipulation skills by following expert-led tutorials, deepening understanding of Python libraries and their applications.
Browse courses on Data Manipulation
Show steps
  • Identify areas where data manipulation skills need improvement.
  • Search and select high-quality tutorials covering advanced techniques.
  • Follow tutorials, taking notes and implementing concepts in practice.
Create a data visualization dashboard using Python libraries
Apply visualization techniques to real-world data by creating an interactive dashboard, solidifying understanding and enhancing communication skills.
Browse courses on Data Visualization
Show steps
  • Gather and clean a suitable dataset for the dashboard.
  • Select and apply appropriate Python libraries for data visualization and dashboard creation.
  • Design and implement the dashboard, ensuring it's user-friendly and visually appealing.
  • Test and refine the dashboard to optimize its functionality and presentation.
Volunteer as a data analyst or visualization specialist
Gain practical experience in data analysis and visualization while contributing to a cause or organization, solidifying skills and building a portfolio.
Browse courses on Data Analysis
Show steps
  • Research and identify organizations or projects seeking data analysis or visualization support.
  • Connect with organizations, express interest, and discuss volunteer opportunities.
  • Contribute data analysis and visualization skills to support projects and initiatives.
  • Reflect on experiences and seek feedback to enhance skills and impact.
Participate in data visualization or data analysis competitions
Challenge oneself in a competitive environment, testing and pushing the boundaries of data visualization and analysis skills.
Browse courses on Data Visualization
Show steps
  • Identify and register for relevant competitions.
  • Study competition guidelines and familiarize oneself with the data.
  • Develop and implement a data visualization or analysis strategy.
  • Submit entries and receive feedback, reflecting on areas for improvement.
Contribute to open-source data visualization projects
Engage with the data visualization community by contributing code or documentation to open-source projects, fostering collaboration and advancing technical skills.
Browse courses on Data Visualization
Show steps
  • Identify open-source data visualization projects that align with interests and skill level.
  • Review project documentation and familiarize oneself with codebase.
  • Propose or select a contribution to make, such as bug fixes, feature enhancements, or documentation improvements.
  • Submit a pull request and engage with the project maintainers to refine and merge contributions.

Career center

Learners who complete مؤثرات عرض البيانات باستخدام لغة بايثون will develop knowledge and skills that may be useful to these careers:
Data Visualization Engineer
A Data Visualization Engineer uses coding and analytical expertise to design charts and dashboards that communicate insights clearly with stakeholders. This course in Data Visualization using Python would be particularly helpful for someone in this role, as it provides practical experience in using Python libraries like Matplotlib, Seaborn, and Vfolium to create compelling data visualizations.
Business Intelligence Analyst
A Business Intelligence Analyst helps organizations make better decisions by analyzing data and presenting insights. This course in Data Visualization using Python would be beneficial for someone in this role, as it provides the skills needed to communicate insights effectively through data visualizations.
Data Scientist
A Data Scientist uses analytical and technical skills to extract insights from data. This course in Data Visualization using Python would be helpful for someone in this role, as it provides the skills needed to communicate insights effectively through data visualizations.
Financial Analyst
A Financial Analyst uses financial data to make investment recommendations and assess the financial health of companies. This course in Data Visualization using Python would be beneficial for someone in this role, as it provides the skills needed to communicate financial data effectively through data visualizations.
Marketing Analyst
A Marketing Analyst uses data to understand customer behavior and optimize marketing campaigns. This course in Data Visualization using Python would be beneficial for someone in this role, as it provides the skills needed to communicate marketing data effectively through data visualizations.
Product Manager
A Product Manager is responsible for the development and launch of new products. This course in Data Visualization using Python would be helpful for someone in this role, as it provides the skills needed to communicate product data effectively through data visualizations.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course in Data Visualization using Python would be helpful for someone in this role, as it provides the skills needed to communicate technical data effectively through data visualizations.
User Experience Designer
A User Experience Designer designs and evaluates the user experience of products. This course in Data Visualization using Python would be helpful for someone in this role, as it provides the skills needed to communicate user experience data effectively through data visualizations.
Web Developer
A Web Developer designs and develops websites and web applications. This course in Data Visualization using Python would be helpful for someone in this role, as it provides the skills needed to communicate web data effectively through data visualizations.
Statistician
A Statistician collects, analyzes, and interprets data to make informed decisions. This course in Data Visualization using Python would be may be helpful for someone in this role, as it provides the skills needed to communicate statistical data effectively through data visualizations.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to make informed decisions. This course in Data Visualization using Python would be may be helpful for someone in this role, as it provides the skills needed to communicate data effectively through data visualizations.
Database Administrator
A Database Administrator manages and maintains databases. This course in Data Visualization using Python may be helpful for someone in this role, as it provides the skills needed to communicate database data effectively through data visualizations.
Information Systems Manager
An Information Systems Manager plans and manages the implementation and use of information systems. This course in Data Visualization using Python may be helpful for someone in this role, as it provides the skills needed to communicate information systems data effectively through data visualizations.
Project Manager
A Project Manager plans and manages projects. This course in Data Visualization using Python may be helpful for someone in this role, as it provides the skills needed to communicate project data effectively through data visualizations.
Technical Writer
A Technical Writer writes technical documentation. This course in Data Visualization using Python may be helpful for someone in this role, as it provides the skills needed to communicate technical data effectively through data visualizations.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in مؤثرات عرض البيانات باستخدام لغة بايثون.
This classic book on data visualization must-read for anyone who wants to learn more about the field. Tufte provides a wealth of insights into how to design effective visualizations that communicate data clearly and effectively.
Comprehensive guide to data visualization with Processing. Tarbell provides a detailed overview of the Processing programming language and its data visualization capabilities. He offers a wealth of examples to show how to use Processing to create effective visualizations.
Provides a comprehensive overview of data visualization principles and techniques. It covers a wide range of topics, from basic chart types to more advanced techniques like interactive visualizations and data storytelling. It's a great resource for anyone who wants to learn more about data visualization.
Comprehensive guide to the ggplot2 data visualization library. Wickham provides a detailed overview of the library's features and functionality, and he offers a wealth of examples to show how to use ggplot2 to create effective visualizations.
Comprehensive guide to the D3.js data visualization library. Murray provides a detailed overview of the library's features and functionality, and he offers a wealth of examples to show how to use D3.js to create effective visualizations.
Comprehensive guide to data visualization with Processing. Reas provides a detailed overview of the Processing programming language and its data visualization capabilities. He offers a wealth of examples to show how to use Processing to create effective visualizations.
Gentle introduction to data visualization for people with no prior experience. Few provides clear and concise explanations of the basic principles of data visualization, and he offers a wealth of practical advice on how to create effective visualizations.

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