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خانه » فروشگاه » Python for Marketing

Python for Marketing

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Take your marketing analytics to the next level with Python. The features that make Python so useful for data scientists are the same ones that marketers can use to better understand their customers, product performance, competition, and marketplace. In this course from Madecraft, learn how to use Python to improve marketing outcomes for your business.

Discover how to import and clean data from various sources, merge data sets, create detailed visualizations, analyze time series data, build custom metrics, and automate key tasks to streamline marketing activities. Along the way, get tips on combining these techniques to conduct market analysis, predict consumer behavior, assess the competition, monitor market trends, and more.

This course was created by Madecraft. We are pleased to host this training in our library.

 


01 - Introduction
  • 01 - Accelerate your marketing with Python
  • 02 - Check out the course prerequisites
  • 03 - Set up your coding environment and tools

    • 02 - 1. Exploring Marketing Data with Python
  • 01 - Identify the role of Python in marketing
  • 02 - Load marketing data in Python
  • 03 - Interpret marketing data in Python

    • 03 - 2. Cleaning Marketing Data with Python
  • 01 - Clean marketing data in Python
  • 02 - Handle missing values in marketing data
  • 03 - Prepare for outlier handling in Python
  • 04 - Handle outliers in marketing data
  • 05 - Reformat marketing data in Python

    • 04 - 3. Manipulating Marketing Data with Python
  • 01 - Manipulate marketing data in Python
  • 02 - Group marketing data by categories
  • 03 - Merge marketing datasets in Python
  • 04 - Filter marketing datasets in Python
  • 05 - Export marketing data as CSV

    • 05 - 4. Visualizing Marketing Data with Python
  • 01 - Visualize marketing data in Python
  • 02 - Create a bar plot in Python
  • 03 - Label the axes in data visualization
  • 04 - Add a title to your data visualization
  • 05 - Use subplots for multiple visualizations
  • 06 - Add a secondary y-axis to your data visualization
  • 07 - Add a legend to your data visualization
  • 08 - Annotate your data visualization
  • 09 - Customize a scatter plot in Python
  • 10 - Create a heatmap in Python

    • 06 - 5. Working with Time Series Data in Python
  • 01 - Find value of time series data in marketing
  • 02 - Prepare the times series data for analysis
  • 03 - Resample the time series data
  • 04 - Create a rolling average plot for time-series marketing data
  • 05 - Plot cost-per-click marketing data
  • 06 - Add dynamic annotations

    • 07 - 6. Calculating Metrics in Python
  • 01 - Calculate click-through rate in Python
  • 02 - Calculate bounce rate in Python
  • 03 - Calculate key performance indicators
  • 04 - Create new metrics for marketing reports

    • 08 - 7. Automating Marketing Tasks with Python
  • 01 - Send personalized emails using Python
  • 02 - Set up helpful alerts with Python
  • 03 - Web scraping for marketing insights

    • 09 - Conclusion
  • 01 - Unlock resources and next steps
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    تاریخ انتشار: ۱۱ مرداد ۱۴۰۳
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