All products developed for today's market are data products - running on data-derived insights to provide the right experience, to the right user, at the right time. Companies like Amazon, Netflix, Google, and more are able to provide personalized and engaging experiences to users because they utilize data science, machine learning, and artificial intelligence to better meet user needs. In the Data Product Manager Nanodegree program, you will hone specialized skills in Product Management, a role with a starting base salary of $125,000. In a series of real-world projects, you will act as a Data Product Manager for a flying taxi company called Flyber to create a data product concept, strategize the data pipeline process, and enhance the product based on user data. Be equipped to build products that leverage data to position customers and businesses to thrive. Hone specialized skills in Data Product Management by learning how to apply data science best practices to build data-driven products backed by scalable data strategies to deliver the right experience to the right users, at the right time.
Prior Data Analysis & Product Management Experience RecommendedSee detailed requirements.
Applying Data Science to Product Management (Available Now!)
As products become more digital, the amount of data collected is increasing. Product managers now have the opportunity to utilize this data to not only enhance existing products, but create completely new ones. Understand the role of data product managers within organizations and how they utilize data science, machine learning, and artificial intelligence to solve problems. Learn how to visualize your data with Tableau for statistical analysis and identify unique relationships between variables via hypothesis testing and modeling. Evaluate the output captured in statistical analyses and translate them into insights to inform product decisions.
Develop a Data-Backed Product Proposal
Establishing Data Infrastructure (Coming Soon!)
Products that collect data from its users can only leverage such data if it gets processed and stored properly. Data product managers need to ensure their products have the appropriate supporting data pipelines in place so that data collected from users can be extracted, transformed, and loaded into a data lake or warehouse that can be used for statistical analysis. Learn about data infrastructure components including data pipelines, data producers, data consumers, data storage, and data processing. Master the nuances of evaluating strategic decisions for data pipeline technology, including security and compliance. Apply learnings to make step-by-step decisions for data infrastructure of an organization. Create solutions for real-world data infrastructure problems and evaluate tradeoffs.
Build a Scalable Data Strategy
Leveraging Data in Iterative Product Design (Coming Soon!)
The best products adapt to market changes over time and are constantly being refined based on user feedback. With a robust data pipeline, the amount of data collected through product usage is extremely valuable to product managers for enhancing their products. Understand which data is best collected through quantitative versus qualitative methods, and how to interpret it. Learn how to apply chi-square tests to determine if results from data analysis are statistically significant. Utilize user data to create user personas that are actionable for development teams to translate into code and for building out user journey maps that describe the stages a user engages with the product along with the associated risks and opportunities. Extract insights from user journey maps to define KPIs of suggested product enhancements and design the relative hypotheses and experiments that are needed to prove the assumptions of product enhancements.