AI Product Leadership Program

Become an AI-Ready Leader: Master LLMs, Generative AI, AI Product Strategy, and MLOps in 6 Months

Gain insights from IIT Kanpur faculty and industry practitioners, combining real-world product experience with cutting-edge AI expertise to help you build scalable, high-impact AI solutions.

Develop a deep understanding of LLMs, Generative AI, AI product strategy, and deployment—equipping you to design, build, and scale AI products that deliver measurable business outcomes.

Work on hands-on projects across the complete AI product lifecycle—from idea to deployment—and culminate your learning through a hackathon conducted during the campus immersion at IIT Kanpur, enabling real-world application and peer collaboration.

Topics Covered

Basics of data and digital literacy

Introduction to logic, algorithms, and problem-solving

Overview of business and technology integration

Learning Outcomes

Build a common baseline across all learners

Gain confidence to engage with technical concepts

Be program-ready from Day 1

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Topics Covered

Introduction to AI, ML, and Deep Learning

Data types, preprocessing, and quality

Supervised and unsupervised learning concepts

Model training, evaluation, and limitations

Learning Outcomes

Understand how AI and ML systems work

Interpret common ML models and outputs

Identify suitable business use cases for AI and ML

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Topics Covered

Large Language Models and foundation models

Prompt engineering basics

Generative AI use cases for text, image, and code

AI agents and autonomous workflows

Learning Outcomes

Understand how Generative AI and LLMs generate outputs

Use GenAI tools effectively for real-world tasks

Conceptualize agent-based AI solutions

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Topics Covered

Identifying AI use cases and problem framing

Data-driven product decision-making

AI product lifecycle and roadmap planning

Measuring success of AI products

Learning Outcomes

Translate business problems into AI solutions

Manage AI products from ideation to launch

Make informed trade-offs in AI-driven products

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Topics Covered

Model deployment basics

Monitoring, versioning, and retraining models

Cloud platforms and AI pipelines

Responsible AI and governance

Learning Outcomes

Understand how AI models are deployed at scale

Identify risks in production AI systems

Appreciate end-to-end AI lifecycle management

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Topics Covered

AI strategy and organizational readiness

Ethical AI and regulatory considerations

Cross-functional collaboration for AI teams

Scaling AI solutions across the enterprise

Learning Outcomes

Lead and influence AI initiatives

Make strategic AI investment decisions

Balance innovation with responsibility

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Topics Covered

Real-world problem statements

End-to-end AI solution design

Team collaboration and execution

Final presentations and evaluations

Learning Outcomes

Apply concepts to real business challenges

Build practical, portfolio-ready AI projects

Demonstrate problem-solving and teamwork skills

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