(588)
2 months
, Beginner
The School Of
Product management offers valuable skills in strategic planning, market research, customer-centricity, and cross-functional collaboration, empowering individuals to lead the development and success of products or services in diverse industries. By gaining expertise in product management, you can drive innovation and contribute to the growth and profitability of businesses.
An AI product manager is responsible for overseeing the development and management of AI-powered products, including defining product vision, prioritizing features, and collaborating with cross-functional teams to ensure successful implementation and delivery.
Steps To Become An AI Product Manager
(588)
2 months
, Beginner
Step 1
(588)
2 months
, Beginner
Skills Covered
Product design sprints, Product prototyping, Product launch, Product scaling, Project evaluation, Solution sketching, Problem validation, Product management basics, Product proposals, Stakeholder management, Product roadmaps, End-user documentation, Feedback loops, A/B testing, Project risk mitigation, Competitive analysis, Stakeholder identification, Decision matrix method, Product validation, User research planning, Evangelization, Press releases, Thinking hats, Crazy 8s, Product success metrics, Product design principles, User interviews, Iterative product design, Technical feasibility evaluation, Affinity mapping, Product storyboarding, Product KPIs, High fidelity prototypes, How might we method, Business model canvasses, Requirements gathering, Return on investment, User personas, Active listening, Professional presentations, Product development cycle, Storytelling, Product requirements documents, Total addressable market, Minimal viable products, Mixed methods market research, Product marketing, Product pricing strategy, Negotiation, Project management frameworks, Prioritization, Cross-functional collaboration, Functional testing, Real-world Testing, Persuasion
Learn More(269)
4 weeks
, Intermediate
Step 2
(269)
4 weeks
, Intermediate
Skills Covered
Model bias analysis, Conversational AI, Data limitations and biases, NLP proficiency, Model performance metrics, Model bias mitigation, NLP business context, GenAI Strategy, Product roadmaps, Dataset annotation, Rice framework, Computer vision business context, Stakeholder management, Types of ML applications, Recommendation engine fluency, AI business context, Recommendation engine business context, AI fluency, Machine learning use cases, Time-Series Forecasting Basics, GenAI Use Cases, Time-Series Forecasting Business Context:
Learn More(588)
2 months
, Beginner
(673)
2 months
, Beginner
(165)
2 months
, Intermediate
(39)
3 months
, Beginner
(81)
3 months
, Beginner
Consumer Goods
Automotive
Technology
Media and Entertainment
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