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AI+ Product Manager™ Self-Paced Learning
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Module 1: Introduction to Artificial Intelligence (AI) for Product Managers
1.0 Introduction: Introduction to Artificial Intelligence (AI) for Product Managers
1.1 Understanding the Basics of Artificial Intelligence
1.2 What is Artificial Intelligence (AI)?
1.3 Branches of Artificial Intelligence
1.4 Deep Dive into AI Applications for Product Management
1.5 The Role of an AI Product Manager
1.6 Importance of AI
1.7 Benefits of AI For Product Development
1.8 Challenges of AI for Product Development
1.9 Summary: Introduction to Artificial Intelligence (AI) for Product Managers
Module 1: E-Book
Quiz
Module 2: Fundamentals of Machine Learning
2.0 Introduction: Fundamentals of Machine Learning
2.1 Introduction: Introduction to Machine Learning
2.2 How Does Machine Learning Work?
2.3 Types of Machine Learning
2.4 Introduction: Data Preparation in ML Model
2.5 Why Do We Need Data Preprocessing?
2.6 Data Preprocessing Steps in Machine Learning
2.7 Hands-on Example of Preprocessing Data Using Pandas And What If We Ignored It?
2.8 Hands-On Exercise
2.9 Summary: Fundamentals of Machine Learning
Module 2: E-Book
Quiz
Module 3: AI Product Development Lifecycle
3.0 Introduction: AI Product Development Lifecycle
3.1 Introduction:Exploring How AI Can Be Leveraged in Ideation and Conceptualization
3.2 The Integration of Artificial Intelligence (AI) into Product Development
3.3 Role of AI in Product Development
3.4 AI Transforming Product Development
3.5 Merits of AI in Product Development And Different Stages of AI Product Development
3.6 Use Cases of AI for Product Development in Different Industries
3.7 Introduction: Prototyping and Testing: Explore Methods for Prototyping and Testing AI-driven Products Effectively
3.8 Methods for Prototyping and Testing AI-Driven Products
3.9 Best AI Tools for Product Managers
3.10 Summary: AI Product Development Lifecycle
Module 3: E-Book
Quiz
Module 04: AI Ethics and Bias
4.0 Introduction: AI Ethics and Bias
4.1 Introduction: Understanding Ethical Considerations: Examine the Ethical Implications of AI Products and the Responsibility of Product Managers
4.2 Bias and Fairness, Privacy and Data Protection, Transparency and Explainability, Accountability and Responsibility, Safety and Reliability, Social Impact and Equity, Regulatory Compliance, Ethical Decision-Making, Continuous Monitoring and Review
4.3 Introduction: Mitigating Bias: Learn Strategies to Identify and Address Bias in AI Algorithms and Products
4.4 Strategies to Identify and Fix Bias in AI Algorithms
4.5 How to Fix Biases in AI and Machine Learning Algorithms?
4.6 Tools to Reduce Bias
4.7 Summary: AI Ethics and Bias
Module 04: E-Book
Quiz
Module 05: AI Implementation Strategies
5.0 Introduction: AI Implementation Strategies
5.1 Introduction: Integration with Existing Products: Explore Methods for Integrating AI Features into Existing Products Seamlessly
5.2 Steps for Successful AI Integration
5.3 Understanding the Potential of AI in Your Product
5.4 Identifying Suitable AI Technologies
5.5 Preparing Your Data for AI Integration
5.6 Implementing AI in Your Product
5.7 Selecting AI Tools and Frameworks
5.8 Developing AI Models And Deploying AI Features
5.9 Monitoring and Improving AI Performance
5.10 Examples of AI Integrations
5.11 Methods to Integrate AI into an App
5.12 Introduction: Stakeholder Management: Understand How to Communicate AI Initiatives Effectively with Stakeholders and Gain their Support
5.13 Key Steps in the Stakeholder Management Process And Stakeholder Management Strategies for Product People
5.14 Benefits of Stakeholder Management for Product People
5.15 Role of Stakeholders in Product Management
5.16 What is it that Stakeholders Really Want?
5.17 Summary: AI Implementation Strategies
Module 05: E-Book
Quiz
Module 06: AI Metrics and Performance Evaluation
6.0 Introduction: AI Metrics and Performance Evaluation
6.1 Introduction: Key Performance Indicators (KPIs): Identify Relevant Metrics for Measuring the Success of AI-driven Products
6.2 Common KPIs for AI
6.3 AI-Enhanced Tracking of KPIs
6.4 Examples of AI Tools for KPI Measurement and Analytics
6.5 Introduction: Performance Evaluation Techniques: Learn Methods for Evaluating the Performance of AI Models and Products
6.6 Introduction to Performance Evaluation
6.7 Techniques used for Performance Evaluation
6.8 Summary: AI Metrics and Performance Evaluation
Module 06: E-Book
Quiz
Module 07: AI Regulation and Compliance
7.0 Introduction: AI Regulation and Compliance
7.1 Introduction: Regulatory Landscape: Explore Current Regulations and Frameworks Relevant to AI Products
7.2 Introduction to the Regulatory Landscape
7.3 AI Regulations in Different Countries
7.4 Key Global Regulations
7.5 Key Regulatory Rules Required for AI
7.6 Entities Most Adversely Affected by AI Regulations
7.7 Impact on AI Companies
7.8 Introduction: Compliance Strategies: Develop Strategies to Ensure AI Products Comply with Regulatory Requirements
7.9 Introduction to AI Regulatory Compliance
7.10 Compliance Strategies
7.11 Summary: AI Regulation and Compliance
Module 07: E-Book
Quiz
Module 08: Future Trends in AI and Product Management
8.0 Introduction: Future Trends in AI and Product Management
8.1 Introduction: Emerging Technologies: Discuss Upcoming Trends and Technologies Shaping the Future of AI and Product Management
8.2 Key Trends to Watch Out For
8.3 Introduction: Strategic Planning: Learn How to Anticipate and Adapt to Future Changes in the AI Landscape to Drive Product Innovation
8.4 Step-by-Step Guide on Strategic Planning
8.5 Strategic Plan
8.6 Summary: Future Trends in AI and Product Management
Module 08: E-Book
Quiz
Resources
AI+ Product Manager Tools
AI+ Product Manager Blueprint
AI+ Product Manager Detailed Curriculum
AI+ Product Manager Resources and References
AI CERTs Exam Guidelines
AI CERTs Exam Guidelines
AI+ Product Manager Examination
AI+ Product Manager Examination
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AI+ Product Manager™ Self-Paced Learning
