Data Science for Marketing Analytics
$84.99 Track price
Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments.
The course starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you’ll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you’ll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you’ll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you’ll apply these techniques to create a churn model for modeling customer product choices.
By the end of this course, you will be able to build your own marketing reporting and interactive dashboard solutions.
About the Author
Tommy Blanchard earned his Ph.D. from the University of Rochester and did his postdoctoral training at Harvard. Now, he leads the data science team at Fresenius Medical Care North America. His team performs advanced analytics and creates predictive models to solve a wide variety of problems across the company.
Courses : 212
Specification: Data Science for Marketing Analytics
7 reviews for Data Science for Marketing Analytics
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Radhe Mohapatra –
very deep explanation and clear understanding
Diliara Khannanova –
Some lessons use methods are not clarified enough. For newbie in the data analysis it is necessary to get more detailed information for methods like PCA. No responses to questions that was arised for particular exercises.
Garima Soni –
voice is not very clear
Udi Menkes –
Was overall good but expected more domain specific real cases for marketing data. Also the relation between the exercises and activities should be described
Sumukh Mysore –
I have not fully formed opinion yet, waiting to get a fuller perspective
Andrew Swimm –
It moves way to fast with the code so it is impossible to code along
Anis Bouderbala –