Udacity is excited to announce that the newest addition to our School of Business — the Data Product Manager Nanodegree program — is open for enrollment.
Earlier this year, we released two of the courses in this program — Applying Data Science to Product Management and Establishing Data Infrastructure — for students to gain early access to the material. Today, the entirety of the Data Product Manager Nanodegree program is now open for enrollment.
Now, with the full Nanodegree program you’ll learn how to apply data science techniques, data engineering processes, and market experimentation tests to deliver customized product experiences.
Quick Review: Data Product Management
Data Product Managers are similar to traditional Product Managers, but instead of managing an application or website, they effectively treat a company’s data strategy and infrastructure as their product. Through data collection and analysis, Data Product Managers propose product features, determine customer happiness, and iterate on product ideas.
The primary function of a data product manager is to balance the strategy, governance, and implementation of data captured by the product, and facilitate the conversations between all impacted stakeholders — executives, engineers, analysts, other product teams, and external customers — who consume the data.
Data Product Managers have been on the rise due to product-led companies increasingly gathering more data to be utilized in everyday decision-making within the business.
Interested in a more thorough review of Data Product Management? Check out our recent blog post Data Product Managers: A Must-Have in the Era of Big Data to learn more.
The Data Product Manager Nanodegree program is ideal for product managers and students who want to learn more about applying data science to product development. Upon completing the Nanodegree program, students will have a thorough understanding of product management through a data-driven lens, including forming data-backed product concepts, establishing data pipelines, and leveraging data to improve user satisfaction.
To get the most out of this program, it’s important for students to have some prior experience with:
- Foundational statistics (mean, median, mode, variance, standard deviation)
- Using Excel with data formulas
- Understanding engineering terms, such as “database” and “algorithm”
Students who enroll in the Data Product Manager Nanodegree program will learn a specialized form of product management that is centered on data-driven products. Upon completing the full Nanodegree program, students will be able to apply data analysis to PM roles, build data infrastructure into existing products, and iterate on their solutions to continuously improve them.
Course 1: Applying Data Science to Product Management
In the first course of the program, students learn how to build out business cases, define metrics, identify data science models to fit their needs, and tie in collected and analyzed data to business problems.
Project: Flying Car Product Proposal for Flyber
The main project in the first course challenges students to use data to strategize which features to add to the first ever flying-car taxi service in NYC.
Students receive datasets consisting of model outputs and aggregated statistics from real taxi rides in New York. With this data, students evaluate the data, identify valuable metrics, and create a product proposal.
This course will give you the practical skills you need to draft a data-backed product proposal that recommends what features the first flying taxi service should have to maximize users’ adoption and generate profits.
Course 2: Establishing Data Structure
In the second course of the program, students learn how to create data pipelines in a product and evaluate them for data quality, reliability, latency, and more.
This course covers various types of databases and gives students tools for understanding which kinds are best for their needs.
After taking this course, you’ll be able to successfully use data to get business insights as well as determine product KPIs.
Project: Scaling Data Strategy for Flyber
The project in the second course builds on the project students created in the first course. Taking Flyber, the flying-car taxi service in NYC, students scale the pipeline in order to collect and analyze data from the product.
First, a Minimum Viable Product (MVP) is defined, then relationships between fields of data are modeled to help make decisions about core product functionality, and finally data is visualized from the pipeline for further analysis.
Course 3: Iterative Design
In the final course of the program, students learn how to evaluate their methods for data collection and analysis and make changes to their pipeline based on their findings.
At the end of this course, students will understand how to make product decisions that they can back up with data.
Project: Enhance User Experience with Data Analysis
In the final project of the Nanodegree program, students build out a research and experimentation plan based on event-level metrics from A/B tests. Students will create hypotheses on how to improve user experience based on datasets and present a plan of recommended experiments for future iterations of the product.
Learning from Top Data Product Managers
To develop this program’s world-class curriculum, we collaborated with professionals from companies, including Zendesk, Expedia, and DISQO. Each of these collaborators contributed guidance and feedback to focus the program on the most in-demand skills. Each of the instructors has extensive data and product management experience.
- JJ Miclat, Sr. Product Manager at Zendesk
- Vaishali Agarwal, Product Manager at Expedia, Inc.
- Anne Rynearson, Sr. Product Manager at DISQO
Are you ready to learn about how data analysis can be used to solve some of the world’s biggest and most complex problems? Enroll today to get started on your journey to becoming a Data Product Manager.