AI+ Product Manager™ (AI+ Product Manager™)

Innovate Products Faster with AI-Enabled Management

  • Product Innovation: Leverage AI to drive product development and market fit
  • Concept to Execution: Explore AI applications in real product lifecycle scenarios
  • Market Advantage: Bridge the gap between tech innovation and customer needs
  • Leadership Ready: Prepare for leading roles in fast-evolving product ecosystems
Google 4.2/5 Average Rating
570+ Learners
Industry Recognized
Certification Body AI CERTs
Delivery Profice
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  • Exam voucher
  • Hands-on labs
  • Certificate
  • Lifetime support
  • Official courseware

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About This Course

Skills You’ll Gain

  • AI Branches Exploration
  • AI Applications in Product Management
  • Role of an AI Product Manager
  • Bridging Technology and Market Solutions
  • AI in Product Development
  • Benefits and Competitive Advantages of AI
  • AI Product Development Processes

Course Information

Course Code AI+ Product Manager™
Duration Self-Paced: 8 hours of content
Delivery Self Paced
Exam Voucher Included

Course Curriculum

  1. 1.1 Understanding the Basics of artificial intelligence
  2. 1.2 Importance of AI

  1. 2.1 Introduction to Machine Learning
  2. 2.2 Data Preparation in ML model

  1. 3.1 Exploring How AI Can Be Leveraged in Ideation and Conceptualization
  2. 3.2 Prototyping and Testing: Explore Methods for Prototyping and Testing AI-driven Products Effectively

  1. 4.1 Understanding Ethical Considerations: Examine the Ethical Implications of AI Products and the Responsibility of Product Managers
  2. 4.2 Mitigating Bias: Learn Strategies to Identify and Address Bias in AI Algorithms and Products

  1. 5.1 Integration with Existing Products: Explore Methods for Integrating AI Features into Existing Products Seamlessly
  2. 5.2 Stakeholder Management: Understand How to Communicate AI Initiatives Effectively with Stakeholders and Gain their Support

  1. 6.1 Key Performance Indicators (KPIs): Identify Relevant Metrics for Measuring the Success of AI-driven Products
  2. 6.2 Performance Evaluation Techniques: Learn Methods for Evaluating the Performance of AI Models and Products

  1. 7.1 Regulatory Landscape: Explore Current Regulations and Frameworks Relevant to AI Products
  2. 7.2 Compliance Strategies: Develop Strategies to Ensure AI Products Comply with Regulatory Requirements

  1. 8.1 Emerging Technologies: Discuss Upcoming Trends and Technologies Shaping the Future of AI and Product Management
  2. 8.2 Strategic Planning: Learn How to Anticipate and Adapt to Future Changes in the AI Landscape to Drive Product Innovation

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

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All You Need to Know

Who Should Attend
  • Product Managers: Enhance your skills by integrating AI into product development processes and drive innovation.
  • Aspiring Product Managers: Gain a strong foundation in AI-driven product management strategies to kickstart your career.
  • Technology Enthusiasts: Leverage AI tools to optimize product strategies and create impactful product experiences.
  • Business Analysts: Apply AI to streamline product development processes and enhance decision-making for better product outcomes.
  • Students & Fresh Graduates: Prepare for a successful career in AI product management by mastering the skills that top companies demand.
Prerequisites
  • Understanding the basics of digital technologies and their influence on various aspects of professional life.
  • Interest in learning about the integration of AI technologies within product development.
  • Participants should have an open mindset towards learning new concepts and technological developments.
Examination

Duration:90 minutes

Passing Score:70% (35/50)

Format:50 multiple-choice/multiple-response questions

Delivery Method:Online via proctored exam platform (flexible scheduling)

Frequently Asked Questions

Product managers, business analysts, and fresh graduates aiming for a career in AI product management.

No — a basic understanding of digital technologies and interest in AI integration within product development is sufficient.

AI-driven product development, prototyping and testing, ethical considerations, stakeholder management, and KPIs for AI products.

Yes — ethical implications and bias mitigation in AI products are covered as a dedicated module.

Emerging AI technologies and strategic planning for the future of AI-driven product management.

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