Customer Analytics in Python
Introducing you to Customer Analytics with Python. You will learn the fundamentals of marketing, as well as the practical skills to analyze customer data and predict the purchase behavior of clients.
With Elitsa Kaloyanova and Nikolay GeorgievStart Course
Customer Analytics in Python is where marketing and data science meet. Data science and marketing are two of the key driving forces that help companies create value and stay on top in today’s fast-paced economy. This course is packed with knowledge, and includes sections on customer and purchase analytics, as well as a deep-learning model, all implemented in Python.
Skills you will gain
What You'll Learn
This course will teach you how to gain authentic insights from the customer's data, as well as how to leverage the power of machine and deep learning to perform customer analytics. This is a highly valuable and rare skillset to have both in data analytics and data science.
- A Brief Marketing Introduction Free5 Lesson 37 Min
- Setting up the environment Free2 Lesson 1 Min
- Segmentation Data Free3 Lesson 16 Min
- Hierarchical Clustering Free2 Lesson 11 Min
- K-means Clustering Free3 Lesson 18 Min
- K-Means Clustering based on Principal Component Analysis Free6 Lesson 23 Min
- Purchase Data Free4 Lesson 14 Min
- Descriptive Analyses by Segments Free4 Lesson 26 Min
- Modeling Purchase Incidence Free9 Lesson 36 MinPurchase Incidence Models. The Model: Binomial Logistic Regression Free Prepare the Dataset for Logistic Regression Free Model Estimation Free Calculating Price Elasticity of Purchase Probability Free Price Elasticity of Purchase Probability: Results Free Purchase Probability by Segments Free Purchase Probability Model with Promotion Free Calculating Price Elasticities with Promotion Free Comparing Price Elasticities with and without Promotion Free
- Modeling Brand Choice Free7 Lesson 34 MinBrand Choice Models. The Model: Multinomial Logistic Regression Free Prepare Data and Fit the Model Free Interpreting the Coefficients Free Own Price Brand Choice Elasticity Free Cross Price Brand Choice Elasticity Free Own and Cross-Price Elasticity by Segment Free Own and Cross-Price Elasticity by Segment - Comparison Free
- Modeling Purchase Quantity Free4 Lesson 19 Min
- Deep Learning for Conversion Prediction Free11 Lesson 55 MinIntroduction to Deep Learning for Customer Analytics Free Exploring the Dataset Free How Are We Going to Tackle the Business Case Free Why do We Need to Balance a Dataset Free Preprocessing the Data for Deep Learning Free Outlining the Deep Learning Model Free Training the Deep Learning Model Free Testing the Model Free Obtaining the Probability of a Customer to Convert Free Saving the Model and Preparing for Deployment Free Predicting on New Data Free
“In this course, you will learn beginner and advanced customer analytics in Python: Marketing theory, PCA, K-means clustering, Elasticity modeling, and Deep neural networks. This is a learning journey that builds a bridge between marketing theory and practical implementation with Python.”
Director at KBC Group
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Customer Analytics in Python
With Elitsa Kaloyanova and Nikolay Georgiev