| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Moderate |
| Duration | 3 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹10749 / $124 |
| Tools | MLOps platforms A/B testing tools Data labeling tools Machine Learning models (Supervised Unsupervised Generative) |
About the AI Product Management Course
AI Product Management is a comprehensive, industry-oriented course tailored for aspiring product managers, entrepreneurs, and technologists.
The program equips learners with end-to-end knowledge of launching AI-driven products—covering everything from problem discovery, data sourcing, model selection, and user experience to team management, deployment, and continuous improvement. It bridges the gap between technical teams and business outcomes in the evolving AI product landscape.
Program Highlights
• Comprehensive coverage of AI Product Management from fundamentals to advanced applications
• Hands-on projects and real-world case studies in AI
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Practical experience with tools: MLOps platforms, A/B testing tools, Data labeling tools, Machine Learning models (Supervised
• Career-oriented training for academic and professional growth in AI
Course Curriculum
Module 1: Foundations of AI Product Management
- Define the pivotal role of an AI Product Manager.
- Distinguish AI products from traditional software solutions.
- Outline the complete AI Product Lifecycle from concept to deployment.
Module 2: Fundamentals of AI & Machine Learning for PMs
- Grasp core AI/ML concepts essential for product management.
- Explore various model types: Supervised, Unsupervised, and Generative AI.
- Understand the critical data lifecycle and its product impact.
- Analyze evaluation metrics and make informed trade-offs.
Module 3: Designing & Scoping AI Solutions
- Identify compelling AI use cases with market potential.
- Scope Minimum Viable Products (MVPs) for AI capabilities.
- Manage data acquisition, labeling, and annotation processes.
- Collaborate effectively with data scientists on model selection.
Module 4: AI Product Design & User Experience
- Design for explainability, trust, and user comprehension.
- Implement Human-in-the-Loop (HITL) design patterns.
- Establish robust feedback loops and active learning systems.
- Address ethical considerations in AI interface design.
Module 5: AI Product Delivery & Operations
- Master model deployment workflows and leverage essential tools.
- Execute A/B testing and establish effective monitoring for AI systems.
- Manage model drift, retraining, and continuous updates.
- Integrate MLOps practices and select appropriate platform choices.
Module 6: AI Product Strategy & Leadership
- Develop a compelling AI product strategy aligned with business goals.
- Create strategic roadmaps for data-driven product development.
- Lead and manage cross-functional AI product teams.
- Navigate legal, compliance, and risk frameworks in AI.
Tools, Techniques, or Platforms Covered
MLOps platforms A/B testing tools Data labeling tools Machine Learning models (Supervised Unsupervised Generative)
Real-World Applications
- Apply AI Product Management skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical AI competencies
- Solve industry-relevant problems using AI Product Management methodologies and tools
- Contribute to open-source projects and collaborative research in AI
- Prepare for competitive examinations, interviews, and professional certifications in AI
Who Should Attend & Prerequisites
- Industry-recognized e-Certification + e-Marksheet from NSTC
- Hands-on training with practical projects and industrial datasets
- Dedicated expert mentorship and doubt resolution
Certification
