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Applying Data Science to Product Management

Course one of three

Hone specialized skills in Data Product Management and learn how to model data, identify trends in data, and leverage those insights to develop data-backed product strategy.

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Enrollments for individual courses are no longer available for this program. Visit our Data Product Manager page to learn more about enrolling in the complete Nanodegree program.

Enroll now and take all three courses!

What you will learn

  1. Applying Data Science to Product Management

    1 month to complete

    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 robust data modeling and analysis in collaboration with data scientists 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.

    Prerequisite knowledge

    1. Introduction to Data Product Management

      Explain the concept and history of data product management, and be able to distinguish the different types of data product managers. Then, identify the various internal stakeholders that data product managers work with. You will understand the fundamentals of general product management from talking to customers, analyzing data, designing high-level solutions, prioritizing work, setting a roadmap, facilitating development, launch communications, and product iteration

      • Granularity, Distribution, and Modeling Data

        Analyze what is being measured in a dataset and explain the benefits of aggregates or roll-up tables. Then, compare and contrast the differences between fact & dimensional tables, and calculate and analyze the distribution of a dataset.

        • Trends, Enrichment, and Visualization

          Identify and differentiate different visualizations, and justify when to apply the right visualization for the appropriate analyses (spatial, temporal, distribution, correlation) - box plot, line chart, donut chart, density map, histogram. Then, implement enriching datasets, and utilize common online repositories for publicly available datasets for analysis.

          • Setting Product Objectives & Strategy

            Interpret data and insights to come up with product objectives. Design KPIs that measure if your products are meeting their objectives and utilize best practices and different techniques for setting up explicit feedback mechanisms. Then, create experiments that generate meaningful results in a timely, resourceful manner and drive instrumentation strategies for proper event data collection.

            • Final Project: Develop a Data-Backed Product Proposal

              A key responsibility of data product managers is analyzing market data to propose new product opportunities. In this project, you will apply the skills acquired in this course to create the MVP launch strategy for the first flying car taxi service, Flyber, in one of the most congested cities in America -- New York City. Your team acquired taxi data for a comparable initial analysis. The dataset contains real taxi drop-offs and pick-ups in New York City. First, you will analyze the existing use cases for and identify temporal, behavioral, and spatial trends of ground-based taxis from the dataset. Next, you will deep-dive into user research data, to understand the general sentiment, desire, concerns, and use cases of a flying cab service to prospective customers. Finally, you will synthesize your insights to create a data-backed product proposal that recommends what features the first flying taxi service should have to maximize consumer delight, adoption and profits.

            Learn with the best.

            Learn with the best.

            • JJ Miclat

              Sr. Product Manager at Zendesk

              JJ is a product leader obsessed with creating simple, novel solutions for the world’s most challenging issues. He’s sunk his teeth into analytics & data product management for Beats Music, Apple, VSCO, & Collective Health.

            All our programs include:

            • Real-world projects from industry experts

              With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

            • Technical mentor support

              Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

            • Career services

              You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

            • Flexible learning program

              Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

            Program offerings

            • Class content

              • Real-world projects
              • Project reviews
              • Project feedback from experienced reviewers
            • Student services

              • Technical mentor support
              • Student community
            • Career services

              • Github review
              • Linkedin profile optimization

            Succeed with personalized services.

            We provide services customized for your needs at every step of your learning journey to ensure your success.

            Get timely feedback on your projects.

            • Personalized feedback
            • Unlimited submissions and feedback loops
            • Practical tips and industry best practices
            • Additional suggested resources to improve
            • 1,400+

              project reviewers

            • 2.7M

              projects reviewed

            • 88/100

              reviewer rating

            • 1.1 hours

              avg project review turnaround time

            Mentors available to answer your questions.

            • Support for all your technical questions
            • Questions answered quickly by our team of technical mentors
            • 1,400+

              technical mentors

            • 0.85 hours

              median response time

            Program details

            Program overview: Why should I take this program?
            • Why should I enroll?
            • How do I know if this program is right for me?
            • What jobs will this program prepare me for?
            • What is the difference between the Product Manager, the Growth Product Manager, the Data Product Manager, and the AI Product Manager Nanodegree programs?
            Enrollment and admission
            • Do I need to apply? What are the admission criteria?
            • What are the prerequisites for enrollment?
            • If I do not meet the requirements to enroll, what should I do?
            Tuition and term of program
            • How is this Nanodegree program structured?
            • How long is this Nanodegree program?
            • Can I switch my start date? Can I get a refund?
            Software and hardware: What do I need for this program?
            • What software and versions will I need in this program?