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Marketing Analytics in Python

Updated 03/2026
Gain the Python skills you need to analyze marketing campaigns, drill into social media data, and use machine learning to predict customer churn.
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PythonProbability & Statistics24 hr4,572

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Track Description

Marketing Analytics in Python

Gain the Python skills you need to make better data-driven marketing decisions. In this track, you’ll learn how to analyze campaign performance, measure customer engagement, and predict customer churn. Working with real-world data, including retail transactions, you'll discover how to analyze social media data, extract insights from text data, and gain market basket analysis skills that will help you better understand your customers. You’ll also use statistical models and machine learning to forecast customer lifetime value. Through hands-on activities, you’ll use popular packages such as pandas, Matplotlib, tweepy, NLTK, seaborn, NumPy, SciPy, and scikit-learn to help you improve your company’s marketing strategy. By the end of the track, you'll be ready to navigate the world of marketing using Python.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Analyzing Marketing Campaigns with pandas

    Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

  • Project

    bonus

    Combating Subscriber Churn with Targeted Marketing

    Leverage machine learning algorithms and models for marketing analytics tasks in a streaming platform.

Marketing Analytics in Python
6 Courses
Track
Complete

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FAQs

Is this Track suitable for beginners?

Yes, this Track is suitable for beginners. It covers the foundations of Python programming while focusing on marketing and analytics related topics. By the end of the track, you will have acquired the skills needed to apply your newfound knowledge to real-world data.

What is the programming language of this Track?

The programming language of this track is Python.

Which jobs will benefit from this Track?

This track is suitable for many marketing and analytics related jobs such as data analyst, marketing analyst, and digital marketing specialist.

How will this Track prepare me for my career?

By completing this Track, you will gain the skills and knowledge needed to apply your newfound knowledge to real-world data. You will be able to use popular packages such as pandas, Matplotlib, tweepy, NLTK, seaborn, NumPy, SciPy, and scikit-learn to help you improve your company's marketing strategy.

How long does it take to complete this Track?

This Track usually takes 28 hours to complete.

What's the difference between a skill track and a career track?

Skill tracks are designed to teach students a specific skill, such as Python programming for data analytics. Career tracks provide broader knowledge and skills that can be used to pursue a new career or help one transition into a new role.

What topics will be covered in this Track?

This Track covers topics such as customer analytics, A/B testing in Python, predicting customer churn in Python, marketing analytics, analyzing social media data, customer segmentation, analyzing marketing campaigns, machine learning for marketing, and market basket analysis.

What packages will I use in this Track?

You will use popular packages such as pandas, Matplotlib, tweepy, NLTK, seaborn, NumPy, SciPy, and scikit-learn to help you improve your company's marketing strategy.

    Join over 19 million learners and start Marketing Analytics in Python today!

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    By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.