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Starts 25 June 2025 04:55

Ends 25 June 2025

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Digital Marketing Analytics

In today's digital age, businesses have unprecedented access to detailed customer data, with the trend of big data only set to increase. Combining marketing history with this vast data pool opens up new opportunities for actionable insights, but requires the right tools and skills. This course leverages real-world applications from various in.
New York University (NYU) via Coursera

New York University (NYU)

18 Courses


Established in 1831, NYU is a prestigious global university in New York City, comprising 17 schools and colleges that offer more than 230 undergraduate, graduate, and professional programs.

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Overview

In today's digital age, businesses have unprecedented access to detailed customer data, with the trend of big data only set to increase. Combining marketing history with this vast data pool opens up new opportunities for actionable insights, but requires the right tools and skills.

This course leverages real-world applications from various industries to teach you how to use these tools and make data-driven decisions for your business.

Participants will delve into interpreting valuable data such as in-store and online transactions, customer surveys, web analytics, pricing, and advertising. You'll learn to tackle critical management challenges, craft relevant hypotheses, and analyze data to draw informed conclusions that support impactful decision-making.

The course also explores the use of artificial intelligence and machine learning as powerful tools to enhance analytical skills and refine decision-making processes.

This comprehensive curriculum is crucial for marketing influencers, digital marketing analysts, and product and brand managers in small to medium enterprises as well as global organizations.

Offered by New York University (NYU) and available on Coursera, this course is categorized under Machine Learning, Big Data, Business Intelligence, A/B Testing, Marketing Analytics, Recommendation Systems, and Search Engine Optimization.


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