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Joseph Santarcangelo
ابدأ تعلم لغة بايثون لعلوم البيانات، بالإضافة إلى البرمجة بوجه عام مع هذه المقدمة البسيطة للمبتدئين في تعلم لغة بايثون. تعتبر بايثون واحدة من أشهر لغات البرمجة في العالم، وهي تشهد إقبالاً غير مسبوق عليها من جانب المحترفين، حيث تمنحهم القدرة على تطبيق المبادئ...
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ابدأ تعلم لغة بايثون لعلوم البيانات، بالإضافة إلى البرمجة بوجه عام مع هذه المقدمة البسيطة للمبتدئين في تعلم لغة بايثون. تعتبر بايثون واحدة من أشهر لغات البرمجة في العالم، وهي تشهد إقبالاً غير مسبوق عليها من جانب المحترفين، حيث تمنحهم القدرة على تطبيق المبادئ الأساسية للغة بايثون لتطوير حلول الأعمال في مختلف الصناعات. ستنقلك هذه الدورة من مستوى المبتدئين إلى البرمجة في بايثون خلال ساعات، وليس من الضروري أن تكون لديك خبرات سابقة في البرمجة! ستتعلم المبادئ الأساسية للغة بايثون، بما في ذلك هياكل البيانات وتحليل البيانات، وتستكمل التدريبات التطبيقية في وحدات الدورة، وتمتلك القدرة على إنشاء مشروع نهائي يبرز مهاراتك الجديدة. مع نهاية هذه الدورة، ستجد سهولة في إنشاء البرامج الأساسية، والعمل باستخدام البيانات، إلى جانب حل المشكلات الواقعية في بايثون. وستكتسب قاعدة معرفية قوية تؤهلك لمستويات تعلم أعلى في هذا المجال، وتُطور مهاراتك لمساعدتك في الارتقاء بحياتك المهنية. يمكن تطبيق هذه الدورة على العديد من البرامج المتخصصة أو برامج الشهادات المهنية. إن استكمال هذه الدورة سيعزز معلوماتك في أيٍ من البرامج التالية: الشهادة المتخصصة في الذكاء الصناعي التطبيقي من IBM التخصص في علوم البيانات التطبيقية الشهادة المتخصصة في علوم البيانات من IBM فور استكمال أيٍ من البرامج السابقة، إلى جانب الحصول على شهادة الإنجاز في التخصص من كورسيرا، ستتلقى أيضًا شارة رقمية من IBM تقديرًا لخبراتك في المجال.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Perfect for total beginners who want to learn Python from scratch
Provides a solid foundation in Python for data science and general programming
Offers hands-on exercises and a final project to apply your skills
Taught by experienced instructors who are recognized in the field
Coursework can be applied towards IBM's specialized programs and certifications
May require additional time and effort for learners with no prior programming experience

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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 بايثون لعلوم البيانات والذكاء الصناعي with these activities:
Review the book 'Python Crash Course' by Eric Matthes
This comprehensive guide will provide you with a solid foundation in Python programming and help you advance your skills.
Show steps
  • Read the book and take notes on key concepts
  • Complete the exercises and projects in the book
  • Review the book's summary and test your understanding
Brush up on Python basics
Review the basics of Python to ensure you have a strong foundation for this course.
Browse courses on Python Basics
Show steps
  • Review Python syntax and data types
  • Practice writing simple Python programs
  • Complete Python tutorials or online exercises
Show all two activities

Career center

Learners who complete بايثون لعلوم البيانات والذكاء الصناعي will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists study data to extract meaningful insights and patterns. They combine programming skills with a deep understanding of statistics and machine learning. This course introduces learners to Python, which is widely used for data analysis and manipulation. Data Scientists who are proficient in Python can leverage it for data cleaning, data exploration, model development, and data visualization. Taking this course can equip learners with foundational knowledge and skills in Python, a valuable tool for success as a Data Scientist.
Data Analyst
Data Analysts gather, clean, and analyze data to identify trends and provide insights for businesses. Proficiency in Python is highly sought after for Data Analysts as it allows them to efficiently manage and manipulate large datasets, perform data analysis, and present findings effectively. This course lays a solid foundation in Python, empowering learners to perform data exploration, data visualization, and statistical analysis, essential skills for success as a Data Analyst.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve complex problems. Python is a key programming language in machine learning, used for data preprocessing, model training, and model evaluation. This course provides a stepping stone for learners who aspire to become Machine Learning Engineers, by introducing them to the basics of Python and its applications in machine learning, such as data wrangling, feature engineering, and model building.
Artificial Intelligence Engineer
Artificial Intelligence Engineers develop and implement AI systems for various applications. They leverage programming languages like Python to build machine learning models, design AI architectures, and integrate AI solutions into existing systems. This course offers a comprehensive introduction to Python, a critical skill for AI Engineers, enabling them to enhance their ability to handle complex data structures, implement algorithms, and construct AI models.
Software Engineer
Software Engineers design, develop, and maintain software applications. Python is widely adopted in software development for its versatility and ease of readability. This course introduces the fundamentals of Python programming, providing Software Engineers with a solid foundation for building robust and efficient software solutions.
Business Analyst
Business Analysts bridge the gap between business stakeholders and technical teams to help businesses make informed decisions. Python is gaining traction among Business Analysts for its data analysis and visualization capabilities. This course offers an introduction to Python, enabling Business Analysts to leverage its strengths for data analysis, process improvement, and stakeholder communication, enhancing their effectiveness in driving business value.
Data Engineer
Data Engineers design and manage data pipelines and infrastructure to support data analytics and machine learning applications. Python is widely used in data engineering for its data manipulation and processing capabilities. This course provides a foundation in Python, equipping Data Engineers with the skills to automate data ingestion, transformation, and storage, enabling them to efficiently build and maintain scalable data pipelines.
Financial Analyst
Financial Analysts use data to assess financial performance and make investment recommendations. Python is gaining popularity in finance for its data analysis and visualization capabilities. This course introduces the basics of Python, enabling Financial Analysts to enhance their data analysis skills, perform financial modeling, and develop automated trading strategies.
Biostatistician
Biostatisticians apply statistical methods to analyze biological and medical data to draw meaningful conclusions. Python is increasingly used in biostatistics for its data analysis capabilities and its extensive libraries for scientific computing. This course introduces the fundamentals of Python, providing Biostatisticians with the necessary skills to perform data analysis, statistical modeling, and visualization of complex biological datasets.
Epidemiologist
Epidemiologists investigate the causes and patterns of disease outbreaks. Python is becoming a valuable tool for Epidemiologists, enabling them to analyze large datasets, create visualizations, and develop predictive models. This course offers an introduction to Python, empowering Epidemiologists to enhance their data analysis skills and contribute to the prevention and control of diseases.
Statistician
Statisticians collect, analyze, and interpret data to provide insights for various fields. Python is widely adopted in statistics for its data manipulation and visualization capabilities. This course introduces the basics of Python, equipping Statisticians with the skills to perform data analysis, statistical modeling, and data visualization, enhancing their ability to draw meaningful conclusions from complex datasets.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. Python is gaining traction among Operations Research Analysts for its optimization and simulation capabilities. This course offers an introduction to Python, providing Analysts with the skills to build models, analyze data, and develop optimization strategies.
Market Research Analyst
Market Research Analysts conduct research to understand market trends, customer behavior, and industry dynamics. Python is becoming a valuable tool for Market Research Analysts, enabling them to analyze large datasets, create visualizations, and develop predictive models. This course offers an introduction to Python, empowering Analysts to enhance their data analysis skills and make informed decisions about market opportunities.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. Python is widely adopted in quantitative finance for its data analysis and modeling capabilities. This course introduces the basics of Python, providing Quantitative Analysts with the skills to perform data analysis, develop trading strategies, and manage risk.
Cybersecurity Analyst
Cybersecurity Analysts protect computer systems and networks from cyber threats. Python is gaining popularity in cybersecurity for its automation and scripting capabilities. This course introduces the basics of Python, enabling Cybersecurity Analysts to automate security tasks, analyze security data, and develop security tools, enhancing their ability to protect organizations from cyberattacks.

Reading list

We've selected nine 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 بايثون لعلوم البيانات والذكاء الصناعي.
Provides a comprehensive introduction to Python for data science, covering topics such as data manipulation, data visualization, and machine learning. It valuable resource for learners who want to gain a deeper understanding of Python's capabilities in data science.
Provides a comprehensive introduction to machine learning using Python. It covers topics such as supervised and unsupervised learning, model evaluation, and feature engineering. It valuable resource for learners who want to gain a deeper understanding of machine learning concepts and techniques.
Provides a comprehensive introduction to deep learning using Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for learners who want to gain a deeper understanding of deep learning concepts and techniques.
Provides a comprehensive introduction to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for learners who want to gain a deeper understanding of deep learning concepts and techniques.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data manipulation, data visualization, and machine learning. It valuable resource for learners who want to gain a deeper understanding of Python's capabilities in data analysis.
Provides a comprehensive introduction to machine learning using Python. It covers topics such as supervised and unsupervised learning, model evaluation, and feature engineering. It valuable resource for learners who want to gain a deeper understanding of machine learning concepts and techniques.
Teaches the fundamentals of data science using Python, without requiring any prior programming experience. It great resource for beginners who want to learn the basics of data science and Python.
Provides an introduction to data science for business professionals. It covers topics such as data mining, machine learning, and data visualization. It valuable resource for learners who want to learn how to use data science to improve business decision-making.
Provides a concise introduction to Python for data science, covering topics such as data manipulation, data visualization, and machine learning. It valuable resource for learners who want to quickly get started with data science using Python.

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