Python for Marketing

سرفصل های دوره

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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تولید کننده: LinkedIn Learning (Lynda)