AI Product Manager Nanodegree Program
助教微信
udacity公众号
Nanodegree key: nd088-cn
Version: 3.0.0
Locale: en-us
驱动 AI 产品商业化落地，用 AI 为业务赋能，成为炙手可热稀缺人才
Content
Part 01 : Welcome to the Nanodegree
- Module 01: 特殊说明
- Lesson 01: 特殊说明本纳米学位的课程内容和实战项目需要使用 Google 相关服务。
Module 02: 学前指导 / First 5 mins
- Lesson 01: 服务说明 / Service Overview 本部分包含重要的课程服务说明，请务必仔细阅读后，再展开后续内容学习。 Below provides detailed descriptions of our services. Please read through before starting with subsequent learning.
- Concept 01: 课程服务与支持 Udacity Service and Support
- Concept 02: 课程保留与维护 Content Access
- Concept 03: Deadline Policy
- Concept 04: Community Guidelines
- Concept 05: Learning Strategies
- Concept 06: Bugcrowd
Part 02 : Introduction to AI in Business
Learn the foundations of AI and how these technologies can learn from data and improve or inform product development.
- Lesson 01: 服务说明 / Service Overview 本部分包含重要的课程服务说明，请务必仔细阅读后，再展开后续内容学习。 Below provides detailed descriptions of our services. Please read through before starting with subsequent learning.
Module 01: Introduction to AI and Machine Learning
- Lesson 01: Welcome
- Lesson 02: Introduction to AI and Machine LearningGet an overview of AI and machine learning and where they are used in industry. This lesson covers terminology and applications of supervised learning, unsupervised learning, and neural networks.
- Concept 01: Overview
- Concept 02: What is AI?
- Concept 03: What Can AI Do?
- Concept 04: The AI Universe
- Concept 05: Why Deep Learning?
- Concept 06: Industry Applications
- Concept 07: Affecting Industry
- Concept 08: Machine Learning Concepts
- Concept 09: Supervised Learning
- Concept 10: Unsupervised Learning
- Concept 11: Unsupervised vs. Supervised Approaches
- Concept 12: Reinforcement Learning
- Concept 13: Neural Networks
- Concept 14: Current State of AI
- Concept 15: Outro
Module 02: Using AI and Machine Learning in Business
- Lesson 01: Using AI and Machine Learning in BusinessHow do you build a successful AI product? Learn which kinds of narrow business cases can stand to benefit the most from machine learning, and identify the components of an effective, AI product team.
- Concept 01: Overview
- Concept 02: AI Approach
- Concept 03: Business Needs
- Concept 04: The Business Case
- Concept 05: Project Statement
- Concept 06: Breaking it All Down
- Concept 07: Metrics
- Concept 08: Metrics Quiz
- Concept 09: Metrics Example: LinkedIn
- Concept 10: Need for AI
- Concept 11: Need for AI Example
- Concept 12: Things to Remember
- Concept 13: Team Overview
- Concept 14: Key Roles
- Concept 15: Project Management
- Concept 16: Summary
Part 03 : Creating a Dataset
Build a custom data annotation job to create novel datasets.
- Lesson 01: Using AI and Machine Learning in BusinessHow do you build a successful AI product? Learn which kinds of narrow business cases can stand to benefit the most from machine learning, and identify the components of an effective, AI product team.
Module 01: Creating a Dataset
- Lesson 01: Data Fit and AnnotationLearn how data can affect the performance of a machine learning model and see how to create your own labeled dataset using FigureEight’s annotation platform.
- Concept 01: Answering Questions with Data
- Concept 02: As Good as the Data
- Concept 03: Data Fit
- Concept 04: Data Collection & Relevance Quiz
- Concept 05: Data Completeness
- Concept 06: Figure Eight’s Data Annotation Platform
- Concept 07: Template Jobs Quiz
- Concept 08: Case Study: Parking Signs & Figure Eight
- Concept 09: The Platform
- Concept 10: Job Design
- Concept 11: Instructions & Examples
- Concept 12: Example Design Quiz
- Concept 13: Test Questions
- Concept 14: Auditing Results
- Concept 15: Planning for Failure
- Concept 16: Planning for Longevity
- Concept 17: Summary of Topics
- Lesson 02: Project: Create a Medical Image Annotation JobGiven a dataset and business goal, design your own data labeling job using Figure Eight’s platform. Project Description - Create a Medical Image Annotation JobProject Rubric - Create a Medical Image Annotation Job
- Concept 01: Project Overview
- Concept 02: Creating a Job with Figure Eight
- Concept 03: Project Materials
Part 04 : Build a Model
Learn how to train and evaluate a neural network using automated machine learning tools.
- Lesson 01: Data Fit and AnnotationLearn how data can affect the performance of a machine learning model and see how to create your own labeled dataset using FigureEight’s annotation platform.
Module 01: Build a Model
- Lesson 01: Training and Evaluating a ModelLearn strategies for training a model from scratch or using transfer learning. Evaluate a model using machine learning tools, such as AutoML.
- Concept 01: Introduction
- Concept 02: Lesson Outline
- Concept 03: Overview of Modeling
- Concept 04: Activation Functions
- Concept 05: Perceptron Quiz
- Concept 06: Activation Function Quiz
- Concept 07: Modeling, Key Points
- Concept 08: Training Data
- Concept 09: A Pet Model
- Concept 10: Training Data is Key
- Concept 11: Training Data Quiz
- Concept 12: Training Data Summary
- Concept 13: Model Evaluation
- Concept 14: Model Evaluation Quiz
- Concept 15: Model Evaluation, Key Points
- Concept 16: Transfer Learning
- Concept 17: Automated ML
- Concept 18: Automated ML vs Custom Modeling
- Concept 19: Automated ML, Summary
- Concept 20: Outro
- Lesson 02: Project: Build a ModelBuild a classification model to classify images of chest xrays using Google AutoML, an automated machine learning tool.Project Description - Build a Model with Google AutoMLProject Rubric - Build a Model with Google AutoML
- Lesson 03: Take 30 Min to Improve your LinkedInFind your next job or connect with industry peers on LinkedIn. Ensure your profile attracts relevant leads that will grow your professional network.Project Description - Improve Your LinkedIn ProfileProject Rubric - Improve Your LinkedIn Profile
- Concept 01: Get Opportunities with LinkedIn
- Concept 02: Use Your Story to Stand Out
- Concept 03: Why Use an Elevator Pitch
- Concept 04: Create Your Elevator Pitch
- Concept 05: Use Your Elevator Pitch on LinkedIn
- Concept 06: Create Your Profile With SEO In Mind
- Concept 07: Profile Essentials
- Concept 08: Work Experiences & Accomplishments
- Concept 09: Build and Strengthen Your Network
- Concept 10: Reaching Out on LinkedIn
- Concept 11: Boost Your Visibility
- Concept 12: Up Next
Part 05 : Measuring Impact and Updating Models
As a product manager, you should be constantly looking to improve your machine learning models and product; learn strategies to mitigate bias, scale a product, and continuously update a model.
- Lesson 01: Training and Evaluating a ModelLearn strategies for training a model from scratch or using transfer learning. Evaluate a model using machine learning tools, such as AutoML.
Module 01: Measuring Business Impact & Mitigating Bias
- Lesson 01: Measuring Business Impact & Mitigating BiasLearn best practices for measuring model success, strategies for mitigating unwanted bias in a model, and scaling a product so that it’s available to a large audience.
- Concept 01: Introduction to Business Impact
- Concept 02: Case Studies and Challenges
- Concept 03: Measuring Success
- Concept 04: Outcome vs. Output
- Concept 05: Outcomes Quiz
- Concept 06: Chatbot Example
- Concept 07: A/B Testing & Versioning
- Concept 08: Monitor Bias
- Concept 09: Text Bias Quiz
- Concept 10: Addressing Unwanted Bias
- Concept 11: Continuous Learning
- Concept 12: Spam Filter
- Concept 13: Model Optimization & Staleness
- Concept 14: Compliance and Ethics
- Concept 15: Privacy-First Approach
- Concept 16: Scaling a Product
- Concept 17: Summary of Skills
- Lesson 02: Case Study: Video AnnotationReview an end-to-end, AI product development cycle from solution ideation to prototyping and testing and finally, product launch (and continuous improvement) for a video annotation product.
- Concept 01: Intro & AI Product Development
- Concept 02: Identify the Business Problem
- Concept 03: Video Annotation Problem
- Concept 04: Prototype & Impact
- Concept 05: Real-Data Prototype
- Concept 06: Product Efficacy Quiz
- Concept 07: Test, Refine -> Final Product
- Concept 08: Release, Measure, Update
- Concept 09: Always Learning
- Concept 10: Conclusion
- Lesson 01: Measuring Business Impact & Mitigating BiasLearn best practices for measuring model success, strategies for mitigating unwanted bias in a model, and scaling a product so that it’s available to a large audience.
- Module 02: Project: Capstone Proposal
- Lesson 01: Project: Capstone ProposalComplete a proposal for a complete AI product of your own design; consider users, data source, design practices, and iteration over time.Project Description - Create an AI Product Business ProposalProject Rubric - Create an AI Product Business Proposal
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