منهجية علم البيانات from Coursera

على الرغم من الزيادة الأخيرة في قوة الحوسبة والوصول إلى البيانات على مدى العقدين الماضيين، فإن قدرتنا على استخدام البيانات في عملية صنع القرار إما فُقدت أو لم يتم تعزيزها على الإطلاق في كثير من الأحيان، فليس لدينا فهم قوي للأسئلة التي يتم طرحها وكيفية تطبيق البيانات بشكل صحيح على المشكلة المطروحة. إن هذه الدورة التدريبية لها غرض واحد، وهو مشاركة المنهجية التي يمكن استخدامها في علم البيانات، للتأكد من أن البيانات المستخدمة في حل المشكلات ذات صلة وتم معالجتها بشكل صحيح لمعالجة السؤال المطروح. وبناءً عليه، ستتعلم في هذه الدورة التدريبية ما يلي: - الخطوات الرئيسية المتضمنة في معالجة مشكلة علم البيانات. - الخطوات الرئيسية المتضمنة في ممارسة علم البيانات، من تشكيل مشكلة عمل أو بحث ملموسة، إلى جمع البيانات وتحليلها، إلى بناء نموذج، وفهم التعقيبات بعد نشر النموذج. - كيف يفكر علماء البيانات! عرض لفترة محدودة: الاشتراك تكلفته 39 دولارًا أمريكيًا فقط كل شهر للوصول إلى مواد ذات درجات وشهادة.

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Suitable for those new to data science, offering a solid foundation in methodology and practice

Taught by experienced instructors Alex Aklson and Polong Lin

Includes hands-on labs and interactive materials for practical application of concepts

Reviews summary

Highly acclaimed data science methodology course

This course on data science methodology has received glowing reviews from students, earning a perfect 5-star rating from all reviewers. Students appreciate the clear and concise instruction, which provides a solid foundation in the field.

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 منهجية علم البيانات with these activities:

Walk through the 'A Gentle Introduction to the Data Science Process' tutorial

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Prepare for this course by getting an overview of the data science process and its key components.

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Visit the tutorial page and read the introduction.
Follow the steps in the tutorial, completing all exercises.
Review the summary and reflect on how these concepts relate to the course.

Read `Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow`

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Build a strong foundation for this course by reviewing real-world applications of machine learning and encountering its tools and techniques.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Scan the table of contents and read the preface.
Read chapters 1 - 3, focusing on understanding the fundamentals of machine learning.

Complete the 'Pandas for Data Analysis' exercises

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Enhance your data analysis skills and reinforce the concepts covered in the course by completing hands-on exercises using Pandas.

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Install Pandas and import it into your Python environment.
Follow the exercises provided in the 'Pandas for Data Analysis' tutorial.
Experiment with different Pandas functions and methods to manipulate and analyze data.

Four other activities

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Create a data dictionary for a real-world dataset

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Develop practical data management skills by creating a data dictionary for a real-world dataset, ensuring data integrity and facilitating data analysis.

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Choose a dataset that aligns with your interests or a specific domain.
Review the dataset and identify key variables and their attributes.
For each variable, define its name, type, format, range, and any relevant metadata.
Organize the information in a structured and easy-to-navigate format, such as a spreadsheet or database.

Organize and review course materials regularly

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Improve retention and understanding by actively organizing and reviewing course materials throughout the learning journey.

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Create a dedicated folder or notebook for course materials.
After each class, take time to整理 and summarize key concepts and notes.
Periodically review your organized materials to reinforce learning.

Form a study group with classmates

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Enhance understanding and retention by actively engaging with peers through discussions and collaborative learning.

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Identify a group of classmates with similar learning goals.
Establish regular meeting times and a communication channel.
Take turns leading discussions, presenting key concepts, and facilitating problem-solving.

Create visual summaries of key data analysis techniques

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Deepen understanding and improve recall by creating visual representations of key data analysis techniques, reinforcing concepts and facilitating communication.

Browse courses on Data Analysis

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Identify a specific data analysis technique covered in the course.
Create a visual representation, such as a flowchart, infographic, or diagram, that explains the technique's steps and key elements.
Share your visual summary with classmates or the instructor for feedback.

Career center

Learners who complete منهجية علم البيانات will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course provides a strong foundation in the methodologies used in data science, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Data Scientists.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. This course provides a strong foundation in the methodologies used by Data Analysts, including data collection, analysis, and visualization. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Data Analysts.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use data to help businesses improve their operations. They analyze data to identify opportunities for improvement and develop recommendations for change. This course provides a strong foundation in the methodologies used by Business Analysts, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Business Analysts.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians use data to solve problems in a variety of fields, including business, medicine, and engineering. They collect, analyze, and interpret data to draw conclusions about the world around us. This course provides a strong foundation in the methodologies used by Statisticians, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Statisticians.

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Machine Learning Engineer

Machine Learning Engineers develop and implement machine learning models to solve business problems. They use data to train models that can make predictions or decisions. This course provides a strong foundation in the methodologies used by Machine Learning Engineers, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Machine Learning Engineers.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

Data Engineers build and maintain the infrastructure that is used to store and process data. They work with data scientists and other data professionals to ensure that data is available and accessible. This course provides a strong foundation in the methodologies used by Data Engineers, including data collection, storage, and processing. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Data Engineers.

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Database Administrator

Database Administrators manage and maintain databases. They ensure that data is stored securely and efficiently and that it is available to users when they need it. This course provides a strong foundation in the methodologies used by Database Administrators, including data storage, security, and backup. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Database Administrators.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use data to create software that is efficient, reliable, and user-friendly. This course provides a strong foundation in the methodologies used by Software Engineers, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Software Engineers.

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Quantitative Analyst

Quantitative Analysts use data to make investment decisions. They analyze data to identify trends and patterns and develop models to predict future market behavior. This course provides a strong foundation in the methodologies used by Quantitative Analysts, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Quantitative Analysts.

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Actuary

Actuaries use data to assess risk. They analyze data to determine the likelihood of future events and develop models to calculate the potential financial impact of those events. This course provides a strong foundation in the methodologies used by Actuaries, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Actuaries.

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Economist

Economists use data to understand the economy. They analyze data to identify trends and patterns and develop models to predict future economic behavior. This course provides a strong foundation in the methodologies used by Economists, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Economists.

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Financial Analyst

Financial Analysts use data to make investment decisions. They analyze data to identify trends and patterns and develop models to predict future market behavior. This course provides a strong foundation in the methodologies used by Financial Analysts, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Financial Analysts.

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Market Researcher

Market Researchers use data to understand consumer behavior. They analyze data to identify trends and patterns and develop models to predict future consumer behavior. This course provides a strong foundation in the methodologies used by Market Researchers, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Market Researchers.

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Operations Research Analyst

Operations Research Analysts use data to solve business problems. They analyze data to identify opportunities for improvement and develop models to optimize business processes. This course provides a strong foundation in the methodologies used by Operations Research Analysts, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Operations Research Analysts.

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Risk Analyst

Risk Analysts use data to assess risk. They analyze data to identify threats and vulnerabilities and develop models to mitigate risk. This course provides a strong foundation in the methodologies used by Risk Analysts, including data collection, analysis, and modeling. Additionally, the course covers how to communicate findings to stakeholders, which is an essential skill for Risk Analysts.

See salaries and explore the career path for Risk Analyst