Artificial Intelligence is transforming every industry, and the ability to manage AI-driven products is now one of the most in-demand skills in the tech landscape. This course provides a complete roadmap for mastering the art and science of AI product management—bridging the gap between data science, engineering, and business strategy.



Expérience recommandée
Ce que vous apprendrez
Develop a clear AI product roadmap and career strategy
Understand core AI/ML capabilities and their business applications
Align AI initiatives with organizational goals and ethical standards
Compétences que vous acquerrez
- Catégorie : Artificial Intelligence
- Catégorie : Artificial Intelligence and Machine Learning (AI/ML)
- Catégorie : MLOps (Machine Learning Operations)
- Catégorie : Generative AI
- Catégorie : Data Infrastructure
- Catégorie : Product Lifecycle Management
- Catégorie : User Interface and User Experience (UI/UX) Design
- Catégorie : Technical Product Management
- Catégorie : Product Design
- Catégorie : Team Performance Management
- Catégorie : Product Strategy
- Catégorie : Data-Driven Decision-Making
- Catégorie : Responsible AI
- Catégorie : Digital Transformation
- Catégorie : AI Product Strategy
- Catégorie : Machine Learning
- Catégorie : Deep Learning
- Catégorie : Commercialization
- Catégorie : Product Management
Détails à connaître

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novembre 2025
19 devoirs
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Il y a 19 modules dans ce cours
In this section, we explore AI, ML, and DL definitions, compare algorithm differences, and examine infrastructure for scalable AI deployment, providing foundational knowledge for effective AI product development.
Inclus
2 vidéos16 lectures1 devoir
In this section, we cover AI model development, NPD stages, and ethical retraining for effective product governance.
Inclus
1 vidéo9 lectures1 devoir
In this section, we compare machine learning and deep learning, focusing on feature extraction, model complexity, and ethical considerations in AI deployment.
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1 vidéo8 lectures1 devoir
In this section, we explore practical AI model implementation, data strategy analysis, and explainable AI design for enterprise applications. Key concepts include AI democratization and the value of generalist skills in real-world product development.
Inclus
1 vidéo7 lectures1 devoir
In this section, we examine AI's role in transforming economic systems, developing AI-driven MVPs, and addressing global challenges in healthcare and governance through ethical and practical applications.
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1 vidéo6 lectures1 devoir
In this section, we explore AI product development stages, team roles, and tech stack investments to build effective AI-native tools with practical applications.
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1 vidéo13 lectures1 devoir
In this section, we explore productizing AI services, emphasizing differences from traditional software, AIOps/MLOps integration, and performance evaluation for scalable, reliable solutions.
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1 vidéo8 lectures1 devoir
In this section, we explore AI customization for verticals, customers, and peer groups, emphasizing domain-specific strategies and data-driven insights for effective product alignment.
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1 vidéo9 lectures1 devoir
In this section, we explore AI-native product design principles, focusing on user and customer journeys, explainability, and clarity to create empathetic, functional AI experiences.
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1 vidéo12 lectures1 devoir
In this section, we explore value metrics, KPIs, and OKRs to measure product success and align strategy with growth goals. We emphasize transparent communication and cost analysis for competitive positioning.
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1 vidéo13 lectures1 devoir
In this section, we explore AI product management strategies, emphasizing alignment, communication, and team collaboration over technical expertise alone.
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1 vidéo7 lectures1 devoir
In this section, we explore AI integration in traditional products and its impact on business strategy and innovation.
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1 vidéo7 lectures1 devoir
In this section, we examine AI trends and growth areas from industry research, evaluate AI readiness, and explore strategies for integrating AI into products and operations for improved outcomes.
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1 vidéo7 lectures1 devoir
In this section, we examine how to evolve products into AI solutions by aligning AI adoption with product strategy and company vision, focusing on strategic planning and risk assessment.
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1 vidéo12 lectures1 devoir
In this section, we cover the evolution of product design and what makes the evolved AI product special.
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1 vidéo8 lectures1 devoir
In this section, we explore adapting existing software products for AI integration, focusing on strategic alignment, feedback loops, and fostering a culture of psychological safety for successful AI transformation.
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1 vidéo6 lectures1 devoir
In this section, we explore pathways to becoming an AI PM, focusing on readiness, role requirements, and interview strategies. It emphasizes customer focus and community engagement for career growth.
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1 vidéo7 lectures1 devoir
In this section, we explore AI PM competencies, challenges, and strategies for long-term career growth in the field.
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1 vidéo9 lectures1 devoir
In this section, we explore developing an AI PM career roadmap, staying informed on AI trends, and expanding professional networks to support continuous growth and adaptability in the field.
Inclus
1 vidéo8 lectures1 devoir
Instructeur

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Foire Aux Questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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