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Hussein ElGhoul
هذا المشروع التوجيهي: تحليل البيانات باستخدام بايثون لتحليل حملات التسويق مخصص لمحللي البيانات الذين يطمحون لإستخدام بيثون لفهم البيانات وتحليلها لأهداف تسويقية. إن هذا المشروع التوجيهي يستغرق حوالي الخمسة وأربعين دقيقة حتى تتمكن فهم كيفية قراءة واكتشاف البيانات بإستخدام بايثون وفهم كيفية رسم البيانات وتحليلها وكيفية استنتاج الارتباط بين عواميد البيانات المختلفة بإستخدام مكتبات بايثون المختلفة.
Register for this course and see more details by visiting:
OpenCourser.com/course/ooky5j/tHlyl
What's inside
Syllabus
ملخص المشروع
هذا المشروع التوجيهي: تحليل البيانات باستخدام بايثون لتحليل حملات التسويق مخصص لمحللي البيانات الذين يطمحون لإستخدام بايثون لفهم البيانات وتحليلها لأهداف تسويقية. إن هذا المشروع التوجيهي يستغرق حوالي الخمسة وأربعين دقيقة حتى تتمكن فهم كيفية قراءة واكتشاف البيانات بإستخدام بايثون وفهم كيفية رسم البيانات وتحليلها وكيفية استنتاج الارتباط بين عواميد البيانات المختلفة بإستخدام مكتبات بايثون المختلفة.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
موجه لمحللي البيانات الذين يطمحون إلى استخدام بايثون في تسويق البيانات
يساعد المتعلمين على فهم كيفية قراءة واكتشاف البيانات باستخدام مكتبات بايثون
يعلم كيفية رسم البيانات وتحليلها باستخدام مكتبات بايثون
Save this course
Save تحليل البيانات باستخدام بايثون: تحليل حملات التسويق to your list so you can find it easily later:
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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 تحليل البيانات باستخدام بايثون: تحليل حملات التسويق with these
activities:
Engage in peer code review sessions
Show steps
Collaborate with peers to review and provide feedback on Python code, fostering code quality and knowledge sharing.
Show steps
-
Form study groups or join online communities for peer code review.
-
Share your code with peers and solicit their feedback.
-
Review and critique the code of your peers, offering constructive suggestions.
-
Integrate feedback into your own code to improve its efficiency and accuracy.
Explore Python packages for data analysis
Show steps
Familiarize with Python libraries for data analysis, such as Pandas, NumPy, and Matplotlib, to enhance technical proficiency.
Show steps
-
Review documentation and tutorials on Python data analysis packages.
-
Install and configure necessary packages in your Python environment.
-
Practice using the packages through guided examples and exercises.
-
Experiment with different techniques for data manipulation and visualization.
Analyze real-world marketing campaign data
Show steps
Interpret and analyze real-world marketing campaign data to hone data analysis skills and gain practical experience.
Show steps
-
Gather real-world marketing campaign data from reputable sources.
-
Clean and preprocess the data to ensure accuracy and consistency.
-
Perform exploratory data analysis to identify trends and patterns.
-
Apply statistical techniques to draw meaningful conclusions from the data.
-
Visualize the results using appropriate charts and graphs.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Simulate marketing campaigns using Python
Show steps
Develop a simulation model to test and evaluate different marketing strategies, enhancing decision-making through data-driven insights.
Show steps
-
Define the simulation parameters and scenarios.
-
Implement the simulation model using Python libraries.
-
Run simulations and analyze the results to identify optimal strategies.
-
Refine the model based on observations and insights gained.
-
Present the simulation findings to stakeholders.
Develop a dashboard for marketing campaign insights
Show steps
Create a visual dashboard to effectively communicate marketing campaign insights, fostering data-driven decision-making.
Show steps
-
Design the dashboard layout and select appropriate visualizations.
-
Integrate data sources and establish data pipelines.
-
Implement interactive features to allow for user exploration.
-
Test and refine the dashboard based on user feedback.
Create a blog post summarizing key concepts
Show steps
Consolidate your understanding by writing a blog post that summarizes key concepts from the course, reinforcing knowledge retention.
Show steps
-
Identify the most important concepts and techniques covered.
-
Research and gather supporting materials.
-
Write a clear and concise blog post outlining the key concepts.
-
Share your blog post with others for feedback and discussion.
Contribute to open-source marketing analytics projects
Show steps
Engage with the open-source community by contributing to projects related to marketing analytics, gaining practical experience and building your portfolio.
Show steps
-
Identify open-source projects related to marketing analytics.
-
Review the project documentation and codebase.
-
Identify areas where you can contribute your skills.
-
Submit pull requests with your contributions.
-
Collaborate with the project maintainers to improve your contributions.
Engage in peer code review sessions
Show steps
Collaborate with peers to review and provide feedback on Python code, fostering code quality and knowledge sharing.
Show steps
Show steps
Show steps
- Form study groups or join online communities for peer code review.
- Share your code with peers and solicit their feedback.
- Review and critique the code of your peers, offering constructive suggestions.
- Integrate feedback into your own code to improve its efficiency and accuracy.
Explore Python packages for data analysis
Show steps
Familiarize with Python libraries for data analysis, such as Pandas, NumPy, and Matplotlib, to enhance technical proficiency.
Show steps
Show steps
Show steps
- Review documentation and tutorials on Python data analysis packages.
- Install and configure necessary packages in your Python environment.
- Practice using the packages through guided examples and exercises.
- Experiment with different techniques for data manipulation and visualization.
Analyze real-world marketing campaign data
Show steps
Interpret and analyze real-world marketing campaign data to hone data analysis skills and gain practical experience.
Show steps
Show steps
Show steps
- Gather real-world marketing campaign data from reputable sources.
- Clean and preprocess the data to ensure accuracy and consistency.
- Perform exploratory data analysis to identify trends and patterns.
- Apply statistical techniques to draw meaningful conclusions from the data.
- Visualize the results using appropriate charts and graphs.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Simulate marketing campaigns using Python
Show steps
Develop a simulation model to test and evaluate different marketing strategies, enhancing decision-making through data-driven insights.
Show steps
Show steps
Show steps
- Define the simulation parameters and scenarios.
- Implement the simulation model using Python libraries.
- Run simulations and analyze the results to identify optimal strategies.
- Refine the model based on observations and insights gained.
- Present the simulation findings to stakeholders.
Develop a dashboard for marketing campaign insights
Show steps
Create a visual dashboard to effectively communicate marketing campaign insights, fostering data-driven decision-making.
Show steps
Show steps
Show steps
- Design the dashboard layout and select appropriate visualizations.
- Integrate data sources and establish data pipelines.
- Implement interactive features to allow for user exploration.
- Test and refine the dashboard based on user feedback.
Create a blog post summarizing key concepts
Show steps
Consolidate your understanding by writing a blog post that summarizes key concepts from the course, reinforcing knowledge retention.
Show steps
Show steps
Show steps
- Identify the most important concepts and techniques covered.
- Research and gather supporting materials.
- Write a clear and concise blog post outlining the key concepts.
- Share your blog post with others for feedback and discussion.
Contribute to open-source marketing analytics projects
Show steps
Engage with the open-source community by contributing to projects related to marketing analytics, gaining practical experience and building your portfolio.
Show steps
Show steps
Show steps
- Identify open-source projects related to marketing analytics.
- Review the project documentation and codebase.
- Identify areas where you can contribute your skills.
- Submit pull requests with your contributions.
- Collaborate with the project maintainers to improve your contributions.
Career center
Learners who complete تحليل البيانات باستخدام بايثون: تحليل حملات التسويق will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts mine and interpret data to help different organizations understand their performance and make better decisions. The course will teach you how to read, explore, and analyze data using Python. This will help you build a foundation for a career as a Data Analyst, where you will be responsible for collecting, cleaning, and analyzing data to identify trends and patterns.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and make recommendations for marketing campaigns. By teaching you how to analyze data using Python, this course will give you the skills you need to succeed in this role. You will learn how to identify trends and patterns in data, which will help you make better decisions about your marketing campaigns.
Business Analyst
Business Analyst
Business Analysts use data to understand how businesses operate and make recommendations for improvement. This course will teach you how to analyze data using Python, which will help you build a foundation for a career as a Business Analyst. You will learn how to identify trends and patterns in data, which will help you make better decisions about your business.
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems. This course will teach you the basics of data science using Python, and will help you build a foundation for a career in this field.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use data to make predictions about the future. This course will teach you the basics of quantitative analysis using Python, and will help you build a foundation for a career in this field.
Statistician
Statistician
Statisticians use data to understand the world around us. This course will teach you the basics of statistics using Python, and will help you build a foundation for a career in this field.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment recommendations. This course will teach you the basics of financial analysis using Python, and will help you build a foundation for a career in this field.
Market Researcher
Market Researcher
Market Researchers use data to understand customer behavior and make recommendations for marketing campaigns. This course will teach you the basics of market research using Python, and will help you build a foundation for a career in this field.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that supports data analysis. This course will teach you the basics of data engineering using Python, and will help you build a foundation for a career in this field.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course will teach you the basics of software engineering using Python, and will help you build a foundation for a career in this field.
Computer Scientist
Computer Scientist
Computer Scientists study the theory and practice of computation. This course will teach you the basics of computer science using Python, and will help you build a foundation for a career in this field.
Data Architect
Data Architect
Data Architects design and manage the data architecture for an organization. This course will teach you the basics of data architecture using Python, and will help you build a foundation for a career in this field.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course will teach you the basics of database administration using Python, and will help you build a foundation for a career in this field.
Systems Analyst
Systems Analyst
Systems Analysts design and implement computer systems. This course will teach you the basics of systems analysis using Python, and will help you build a foundation for a career in this field.
Web Developer
Web Developer
Web Developers design and develop websites. This course will teach you the basics of web development using Python, and will help you build a foundation for a career in this field.
For more career information including salaries, visit:
OpenCourser.com/course/ooky5j/tHlyl
Reading list
We've selected ten 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
تحليل البيانات باستخدام بايثون: تحليل حملات التسويق.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data cleaning, data manipulation, and data visualization. It valuable resource for learners who want to gain a strong foundation in Python for data analysis.
Save
Provides a comprehensive overview of marketing management, covering topics such as marketing strategy, marketing planning, and marketing research. It valuable resource for learners who want to gain a strong foundation in marketing management and its applications.
Provides a practical guide to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It valuable resource for learners who want to gain hands-on experience with machine learning.
Provides a comprehensive overview of data warehousing, covering topics such as data modeling, data integration, and data quality. It valuable resource for learners who want to gain a strong foundation in data warehousing and its applications.
Provides a comprehensive overview of machine learning algorithms and techniques, using Python as the programming language. It valuable resource for learners who want to gain a strong foundation in machine learning and its applications.
Provides a practical introduction to email marketing, covering topics such as data collection, data analysis, and data visualization. It valuable resource for learners who want to gain a hands-on understanding of email marketing.
Provides a practical introduction to search engine optimization, covering topics such as data collection, data analysis, and data visualization. It valuable resource for learners who want to gain a hands-on understanding of search engine optimization.
Provides a practical introduction to web analytics, covering topics such as data collection, data analysis, and data visualization. It valuable resource for learners who want to gain a hands-on understanding of web analytics.
Save
Provides a practical introduction to data mining, covering topics such as data collection, data analysis, and data visualization. It valuable resource for learners who want to gain a hands-on understanding of data mining.
Provides a practical introduction to data science, covering topics such as data cleaning, data manipulation, and data visualization. It valuable resource for learners who want to gain a hands-on understanding of data science.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ooky5j/tHlyl
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Effort
1 hour 30 minutes
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Hussein ElGhoul
Language
العربية
Good to know
موجه لمحللي البيانات الذين يطمحون إلى استخدام بايثون في تسويق البيانات
يساعد المتعلمين على فهم كيفية قراءة واكتشاف البيانات باستخدام مكتبات بايثون
يعلم كيفية رسم البيانات وتحليلها باستخدام مكتبات بايثون
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