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AI+ Product Manager Fundamentals™

Course code: NPAP250

Formerly known as AI+ Product Manager™

Innovate Products Faster with AI-Enabled Management

  • Product Innovation: Harness AI to accelerate product development and achieve stronger market fit.
  • Concept to Execution: Explore practical AI applications across real-world product lifecycle stages.
  • Market Advantage: Close the gap between technological innovation and evolving customer expectations.
  • Leadership Ready: Build the capabilities needed to take on leading roles in fast-moving product ecosystems.
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI Product Development Expertise

Learners will gain a comprehensive understanding of the AI product development lifecycle, from ideation to deployment, ensuring they can manage AI projects effectively.

Strategic AI Implementation

Students will learn how to strategize the integration of AI into products, including selecting the right AI technologies and approaches to enhance product value and user experience.

Ethics and Regulatory Compliance

Learners who will go through this course will have the knowledge on navigating the ethical considerations and regulatory landscapes associated with AI, crucial for responsible product management.

Performance Metrics and Evaluation

Learners will develop the ability to set and evaluate AI performance metrics, helping them measure the impact and effectiveness of AI features within their products.

Course structure

Certification Overview

Module 1: Introduction to Artificial Intelligence (AI) for Product Managers

  • 1.1 Understanding the Basics of artificial intelligence
  • 1.2 Importance of AI

Module 2: Fundamentals of Machine Learning

  • 2.1 Introduction to Machine Learning
  • 2.2 Data Preparation in ML model

Module 3: AI Product Development Lifecycle

  • 3.1 Exploring How AI Can Be Leveraged in Ideation and Conceptualization
  • 3.2 Prototyping and Testing: Explore Methods for Prototyping and Testing AI-driven Products Effectively

Module 4: AI Ethics and Bias

  • 4.1 Understanding Ethical Considerations: Examine the Ethical Implications of AI Products and the Responsibility of Product Managers
  • 4.2 Mitigating Bias: Learn Strategies to Identify and Address Bias in AI Algorithms and Products

Module 5: AI Implementation Strategies

  • 5.1 Integration with Existing Products: Explore Methods for Integrating AI Features into Existing Products Seamlessly
  • 5.2 Stakeholder Management: Understand How to Communicate AI Initiatives Effectively with Stakeholders and Gain their Support

Module 6: AI Metrics and Performance Evaluation

  • 6.1 Key Performance Indicators (KPIs): Identify Relevant Metrics for Measuring the Success of AI-driven Products
  • 6.2 Performance Evaluation Techniques: Learn Methods for Evaluating the Performance of AI Models and Products

Module 7: AI Regulation and Compliance

  • 7.1 Regulatory Landscape: Explore Current Regulations and Frameworks Relevant to AI Products
  • 7.2 Compliance Strategies: Develop Strategies to Ensure AI Products Comply with Regulatory Requirements

Module 8: Future Trends in AI and Product Management

  • 8.1 Emerging Technologies: Discuss Upcoming Trends and Technologies Shaping the Future of AI and Product Management
  • 8.2 Strategic Planning: Learn How to Anticipate and Adapt to Future Changes in the AI Landscape to Drive Product Innovation

Optional Module: AI Agents for Product Management

  • 1. Understanding AI Agents
  • 2. Case Studies
  • 3. Hands-On Practice with AI Agents

Prerequisites

  • A basic understanding of digital technologies and their role in professional environments.
  • An interest in how AI can be integrated into product development processes.
  • An open and adaptive mindset toward learning emerging concepts and technological advancements.

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