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DataCamp

Marketing Analytics in Python

via DataCamp

Overview

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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.

Syllabus

  • Analyzing Marketing Campaigns with pandas
    • Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
  • 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.
  • Market Basket Analysis in Python
    • Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
  • 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.
  • Customer Segmentation in Python
    • Learn how to segment customers in Python.
  • Marketing Analytics: Predicting Customer Churn in Python
    • Learn how to use Python to analyze customer churn and build a model to predict it.
  • Combating Subscriber Churn with Targeted Marketing

Taught by

Mark Peterson, Alex Hanna, Karolis Urbonas, Jack Rosok, and Isaiah Hull

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