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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

    Prior Data Analysis & Product Management Experience Recommended

    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.

            • Real-time support

              On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.

            • 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

              • Student community
              • Real-time support
            • 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

            Program details

            Program overview: Why should I take this program?
            • Why should I enroll?

              Product Manager is a top 5 job on LinkedIn's Most Promising Jobs for 2019, and one of the most coveted roles in large tech enterprises, as well as entrepreneurial startups. 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 and be equipped to build products that leverage data to position customers and businesses to thrive. This program is designed for students who want to assume key leadership roles in data product development and strategy in their company.

              Leverage market data to amplify product development. Learn how to apply data science techniques, data engineering processes, and market experimentation tests to deliver customized product experiences. Begin by leveraging the power of SQL and Tableau to inform product strategy. Then, develop data pipelines and warehousing strategies that prepare data collected from a product for robust analysis. Finally, learn techniques for evaluating the data from live products, including how to design and execute various A/B and multivariate tests to shape the next iteration of a product.

            • How do I know if this program is right for me?

              This Nanodegree program is perfect for existing Product Managers, Data Science professionals, and Engineers who are already in data or product-focused roles and want to further their skillset, as well as those who wish to break into the data product domain and help build products that utilize data to provide better product experiences.

              In most of the digital products, data is used to enhance product lines, better meet customer needs, make products that customers actually want, or create for a more personalized experience. Data that are collected from a product can be fed into machine learning algorithms and used to improve the overall user journey. If you want to build data-driven products backed by scalable data strategies to deliver the right experience to the right users, at the right time, then this Nanodegree program is right for you.

            • What jobs will this program prepare me for?

              This program will equip you with the skills to assume data product manager roles. You’ll learn directly from experienced Product Managers at Zendesk, Expedia, and DISQO, who have constructed this Nanodegree program to equip you with the most in-demand and relevant industry skills.

            • What is the difference between the Product Manager, the Growth Product Manager, the Data Product Manager, and the AI Product Manager Nanodegree programs?

              The Product Manager Nanodegree program will equip you with the foundational skills to assume entry-level product manager roles. You’ll learn directly from experienced Product Managers at Uber and Google, who have constructed this Nanodegree program to equip you with the most in-demand and relevant industry skills. This Nanodegree program teaches the core skill set required in all Product Manager roles, which is the foundation for more specialized roles like Growth Product Manager, Data Product Manager, AI Product Manager, and more.

              The AI Product Manager Nanodegree program is meant for product managers that are responsible for building and deploying AI products. The AI PM Nanodegree program is focused on the hands-on tasks of scoping a data set, training a model, and evaluating the performance of the model.

              The Growth Product Manager Nanodegree program is meant for experienced Product Managers who are looking to specialize their skills in product management and be equipped to fill growth-focused roles. You’ll learn how to grow the user base of your product, get customers engaged and activated as quickly as possible, and monetize your product to have it generate revenue.

              The Data Product Manager Nanodegree program is meant for experienced Product Managers who are looking to specialize their skills in product management and be equipped to fill data-focused roles in the development and strategy behind data products. You'll learn how to build an MVP launch strategy for a new service product that utilizes market insights extracted from extensive data analyses and visualizations, develop a data model with corresponding data pipelines and transformations to evaluate user activity of a product, and identify key behavioral and descriptive attributes of users to construct hypotheses for new product features and experiments to validate these hypotheses.

            Enrollment and admission
            • Do I need to apply? What are the admission criteria?

              There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.

            • What are the prerequisites for enrollment?

              No prior experience with data modeling and data engineering is required. However, a basic understanding of data terminology (i.e. big data, database, algorithms, etc.), some experience with data analysis (basic SQL & Tableau), and a general understanding of product management is helpful.

            • If I do not meet the requirements to enroll, what should I do?

              The following Nanodegree programs are not necessary to complete before starting this program, but could be helpful if you would like to prepare.

              You can check out the Product Manager Nanodegree program, SQL Nanodegree program, or the Programming for Data Science with Python Nanodegree program.

            Tuition and term of program
            • How is this Nanodegree program structured?

              The Data Product Manager Nanodegree program is comprised of content and curriculum to support three projects. Once you subscribe to a Nanodegree program, you will have access to the content and services for the length of time specified by your subscription. We estimate that students can complete the program in three months, working 10 hours per week.

              Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.

            • How long is this Nanodegree program?

              You will have access to this Nanodegree program for as long as your subscription remains active. The estimated time to complete this program can be found on the webpage and in the syllabus, and is based on the average amount of time we project that it takes a student to complete the projects and coursework. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.

            • Can I switch my start date? Can I get a refund?

              Please see the Udacity Program FAQs for policies on enrollment in our programs.

            Software and hardware: What do I need for this program?
            • What software and versions will I need in this program?

              You will need to use SQL, Tableau, Google Slides or Microsoft PowerPoint, and Google Sheets or Microsoft Excel, as well as have access to the internet and a 64-bit computer. You will also need access to a computer for which the requirements are:

              Minimum browser requirements are:

              • Chrome 49+
              • Firefox 57+
              • Safari 10.1+ (Apple - macOS)
              • Edge 14+ (Windows)
              Minimum operating system (OS) requirements are:
              • Windows 8.1 or later
              • Apple MacOS 10.10 (Yosemite) and later
              • Any Linux OS that supports the browsers mentioned above
              • Any Chrome OS that supports the browsers mentioned above