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Estimated Time
2 Months
At 5-10 hours/week
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What You Will Learn
Syllabus
AI Product Manager
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Prerequisite Knowledge
No prior experience is required.See detailed requirements.
Introduction to AI in Business
Gain foundational knowledge of AI and machine learning, how to develop a business case for an AI application, and how and when to use AI in a product.
Creating a Dataset
A high-quality training data set is essential for machine learning models. Learn how to create a high-quality dataset, including how well the data fits a particular use case.
Create a Medical Image Annotation Data Set with AppenBuilding a Model
Learn how a neural network produces a decision and how “training” works. You’ll also learn how to use training data and how to evaluate the results of a model.
Build a Model with Google AutoMLMeasuring Impact and Updating Models
Learn how to measure post-deployment impact, and how to make data-informed improvements on your model. You’ll also learn how to avoid unwanted bias, ensure security and compliance, and how to scale your product.
Capstone Project
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.
Personal career coach and career services
You’ll have access to career coaching sessions, interview prep advice, and resume and online professional profile reviews to help you grow in your career.
Flexible learning program
Get a custom learning plan tailored to fit your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
Program OfferingsFull list of offerings included:
Enrollment Includes:
Class content
Real-world projects
Project reviews
Project feedback from experienced reviewers
Student Services
Technical mentor support
New
Student community
Improved
Career services
Personal career coaching
New
Interview preparations
Resume services
Github review
LinkedIn profile review
Succeed with Personalized Services
We provide services customized for your needs at every step of your learning journey to ensure your success!
Experienced Project Reviewers
Project Reviewers
Technical Mentor Support
Technical Mentor Support
Personal Career Coach
Career Coaching
Get personalized feedback on your projects
Reviews By the numbers
2000+ project reviewers
1.8M projects reviewed
4.85/5 reviewer ratings
3 hour avg project review turnaround time
Reviewer Services
- Personalized feedback
- Unlimited submissions and feedback loops
- Practical tips and industry best practices
- Additional suggested resources to improve
Learn with the best
Alyssa Simpson-Rochwerger
VP of AI and Data at Appen
Alyssa is a customer-driven product leader with proven experience in scaling products from conception to large-scale ROI. As Director of Product Management at IBM Watson, she oversaw the development of a large portfolio of AI products.
Meeta Dash
VP of Product at Appen
Meeta Dash is VP of Products at Appen, which builds AI products to help enterprises solve real world use cases. An NIT India BTech and UCDavis MBA, she's built AI and Voice/Video products at Cisco, Tokbox and CA.
Kiran Vajapey
Senior HCI Developer at Appen
Kiran Vajapey is an HCI Developer working on creating new products and interfaces to advance AI in industry. Kiran has a Master's in CS from Cornell and has previous experience in HR Tech, Fintech, and product architecture.
Kirsten Gokay
Product Manager at Appen
Kirsten received her Bachelor’s degree in Linguistics from UC Davis. With a background in Customer Success, she’s passionate about solving complex problems with easy-to-use products.
Andrea Butkovic
Product Manager at Appen
Andrea Butkovic is a product manager focused on creating machine learning powered annotation tools for AI teams at Appen. Andrea has a degree in Geography from UC Berkeley with a focus in Cartography.
Get Started
Become an AI Product Manager
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Develop products that leverage AI by learning how AI can influence your business, how to scope and train AI models, and how to measure success.
Average Time
On average, successful students take null months to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
- Personal career coach & career services
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null months access
per month
Start learning today! Switch to the monthly price afterwards if more time is needed.
Pay as you go
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Start Learning Today! Get maximum flexibility to learn at your own pace.
Related Nanodegree Programs
Program Details
PROGRAM OVERVIEW - WHY SHOULD I TAKE THIS PROGRAM?
Why should I enroll?
AI is changing the world around us at an astounding pace. For many, Artificial Intelligence remains a mystery, and how to leverage this technology is not always clear.
This program is designed for students who want to take advantage of AI, but don’t want or need to learn the full technical implementation of neural networks and machine learning models. You’ll learn how to leverage AI in the business world, from scoping datasets, testing machine learning models, and crafting a proposal for a new product powered by AI. Along the way you’ll build fluency in AI concepts.What jobs will this program prepare me for?
This program is designed to upskill practicing product managers to build AI-powered products and bring value to their business using AI.How do I know if this program is right for me?
This program is intended for anyone who wants to gain fluency and understanding of AI use cases. If you want to learn how to leverage AI, including how to build a dataset and how to evaluate different machine learning models without needing to code, this program is for you.
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?
There are no technical prerequisites. This course is intended for professionals who have some familiarity with product management and basic data analysis.If I do not meet the requirements to enroll, what should I do?
If you need to review basic data analytics skills, we recommend the Intro to Descriptive Statistics course.
Tuition and Term of Program
How is this Nanodegree program structured?
The AI Product Manager Nanodegree program is comprised of content and curriculum to support 3 (three) projects. We estimate that students can complete the program in two (2) 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.Can I switch my start date? Can I get a refund?
Please see the Udacity Nanodegree program FAQs for policies on enrollment in our programs.
What software and versions will I need for this program?
What software and versions will I need for this program?
For this Nanodegree program, you will need a desktop or laptop computer running recent versions of Windows, Mac OS X, or Linux, and an unmetered broadband Internet connection. There are no additional hardware or software requirements for this program, other than those outlined on Udacity's general Technology Requirements page.
Why take this Nanodegree program?
AI is changing every industry faster than we can keep up with it. This program will teach you how to make AI products deliver clear business value, by learning a proven process for developing AI products. You’ll build fluency in AI by reviewing case studies, creating a data set on Figure Eight’s platform, and building a model using Google AutoML. You’ll end this program with skills to ideate, develop, evaluate, and implement new products driven by AI. This is intended for product managers and business leaders who want to drive value for their business using AI. *You’ll make sure your product is successful by learning about scalability, compliance, and monitoring potential bias in your model.*
