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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.

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Loved by learners at thousands of companies

1
Analyzing Marketing Campaigns with pandas

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

4 hours

Jay Rosok Headshot

Jay Rosok

Data Scientist at Spotify

2
Analyzing Social Media Data in Python

In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

4 hours

Alex Hanna Headshot

Alex Hanna

Computational Social Scientist

3
Market Basket Analysis in Python

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

4 hours

Isaiah Hull Headshot

Isaiah Hull

Economist

4
Machine Learning for Marketing in Python

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

4 hours

Karolis Urbonas Headshot

Karolis Urbonas

Head of Machine Learning and Science

5
Customer Segmentation in Python

Learn how to segment customers in Python.

4 hours

Karolis Urbonas Headshot

Karolis Urbonas

Head of Machine Learning and Science

6
Marketing Analytics: Predicting Customer Churn in Python

Learn how to use Python to analyze customer churn and build a model to predict it.

4 hours

Mark Peterson Headshot

Mark Peterson

Senior Data Scientist at Alliance Data

7
Customer Analytics and A/B Testing in Python

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

4 hours

Ryan Grossman Headshot

Ryan Grossman

Data Scientist at EDO Inc.

8
Combating Subscriber Churn with Targeted Marketing

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

2 hours

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Instructors

  • Jay Rosok Headshot
    Jay RosokData Scientist at SpotifySee Jay Rosok's Portfolio
  • Alex Hanna Headshot
    Alex HannaComputational Social ScientistSee Alex Hanna's Portfolio
  • Isaiah Hull Headshot
    Isaiah HullEconomistSee Isaiah Hull's Portfolio
  • Karolis Urbonas Headshot
    Karolis UrbonasHead of Machine Learning and ScienceSee Karolis Urbonas's Portfolio

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