AI BootCamps (6 Courses)
Career Oriented
Course Category Career Oriented
Course Category 
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Learners
Cohorts
Enterprises
The product management role is shifting faster than any other in tech, i.e., from backlog custodian to AI system orchestrator. Only 25% of PM tools today have meaningful agentic capabilities, which means the window to get ahead of this curve is open right now. This 16-hour live course applies Gen AI and Agentic AI across the complete product lifecycle in 12 modules: user research and discovery, opportunity sizing, user story writing, backlog management, roadmapping, hypothesis testing, data analytics, release planning, stakeholder communication, competitive analysis, go-to-market, and retrospectives with both levels covered in every session: Gen AI to work faster, Agentic AI to work autonomously.
You leave with 200+ PO and PM-specific prompts, 6 completed capstone deliverables built during the course, and the exact skill that separates a standard product owner from an AI-fluent one: the ability to design, direct, and evaluate AI-powered product workflows without writing a single line of code.
Discovery to retrospective, Gen AI and Agentic AI applied at every stage
Feedback synthesis agents that process thousands of support tickets, reviews, and interviews in minutes
AI-powered roadmap scenario modelling that simulate trade-offs and prioritise with confidence
200+ tested prompts for PRDs, user stories, release notes, competitive analysis, and stakeholder comms
24 PDUs and 24 SEUs valid for credential renewal
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Use AI to accelerate product discovery — synthesising user research, analysing market signals, and identifying opportunity spaces faster than traditional methods allow.
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Use AI to build, pressure-test, and communicate product strategy and roadmaps with greater speed and stakeholder clarity.
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Use AI to write better user stories faster, maintain a healthy backlog, and ensure every item has the clarity teams need to build the right thing.
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Use AI to make faster, more defensible prioritisation decisions — removing gut feel and replacing it with structured, evidence-based analysis.
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Use AI to manage the most time-consuming part of a PO’s role — keeping stakeholders informed, aligned, and engaged.
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Use AI to deepen your understanding of users — analysing behaviour data, synthesising feedback, and making evidence-based UX decisions faster.
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Use AI to define the right metrics, track them efficiently, and translate data into clear product decisions and compelling OKR progress narratives.
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Use AI to make sprint planning faster, more accurate, and more collaborative — and keep delivery teams aligned throughout execution.
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Use AI to plan, coordinate, and execute product launches more effectively — from positioning through cross-functional alignment and post-launch analysis.
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Use AI to make retrospectives more insightful, track improvement actions, and embed a culture of continuous learning in the product team.
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Use AI to create and maintain the documentation that ensures teams always have accurate, accessible, and current product information.
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Apply every skill from the course to a realistic end-to-end product management scenario across discovery, planning, delivery, and launch.
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To fast-track your career and achieve
There is no exam for this workshop.
This course really helped me to upgrade my skills and now I am able to handle projects easily. I highly recommend this workshop.
I’ve taken dozens of PM courses—none this practical. I walked away with real tools and a real edge.
This course is totally worth it. I highly recommend this to the one who wants to improve their skillset.
Using ChatGPT ad-hoc and applying AI systematically across every stage of product work are very different things. The course covers 12 product management domains — not just story writing — and introduces Agentic AI, where systems run autonomously in the background rather than waiting for your next prompt. The jump from occasional prompting to structured AI workflows across discovery, backlog, roadmap, release, and strategy is the jump that makes AI a genuine career advantage, not a convenience tool.
A standard PO manages the backlog, writes stories, and represents the customer. An AI-fluent PO does all of that — and also designs and directs AI-powered workflows: feedback synthesis agents that process thousands of customer signals automatically, roadmap scenario models that simulate trade-offs before the team debates them, and release communication drafts that take minutes instead of hours. The AI-fluent PO makes higher-quality product decisions faster, and has the data to defend them. That distinction is increasingly visible in hiring decisions and compensation.
No coding, no technical background required. The course teaches you how to direct AI systems — not build them. You will work with ChatGPT and Claude through a browser, using structured prompting techniques that produce professional outputs. The AI Foundations course (4 hours) is the only prerequisite, and it is designed to be accessible regardless of your technical background.
The human judgment in discovery — deciding what matters, what to ask, and what to build — remains yours. What AI changes is the scale and speed of the input layer. Instead of reading 50 support tickets manually, an agent synthesises patterns across 5,000. Instead of spending three hours crafting an interview guide, AI produces a structured first draft in minutes for you to refine. The course covers both: Gen AI for accelerating your own discovery work, and Agentic AI for building feedback pipelines that run continuously without manual initiation.
The six capstone deliverables are: an AI-assisted opportunity canvas and user persona set; a full user story map with acceptance criteria written using structured prompting; a roadmap scenario analysis with AI-generated prioritisation rationale; a release communication package including notes, stakeholder email, and sprint review deck; a competitive landscape analysis built with AI research agents; and a retrospective insights report with a 90-day personal AI adoption plan. All are built during the course using a realistic product scenario and are yours to keep and adapt for real work.
Different role, different deliverables, different focus. The Project Management course covers the project lifecycle — initiation, planning, EVM, vendor management, closure. This course covers the product lifecycle — discovery, opportunity sizing, backlog, roadmapping, hypothesis testing, go-to-market, and retrospectives. The PM course is for people delivering projects; this course is for people defining and evolving products. There is minimal overlap between the two.
PDUs count toward PMP and CAPM renewal with PMI, categorised under Technical Education. SEUs count toward CSPO and A-CSPO renewal with Scrum Alliance, PSPO renewal with Scrum.org, and SAFe POPM credential maintenance. If you hold multiple credentials, the same 24 hours applies to each body’s renewal requirements — check with your specific certification body for current rules, but for most PO and PM credentials this course covers a significant portion of a full renewal cycle in a single course.
With structured prompting and the right context, AI-generated roadmap analysis is genuinely useful — not generic. The course teaches you how to feed AI your specific constraints: team capacity, business goals, customer data, and competitive signals, and how to structure prompts that produce scenario comparisons you can actually use in planning sessions. The goal is not to let AI decide your roadmap — it is to use AI to prepare the analysis that makes your decision faster, better-supported, and easier to defend to stakeholders.
Yes — Business Analysts working in Agile environments will find significant overlap with their day-to-day work. The modules on user story writing, acceptance criteria, stakeholder communication, requirements documentation, and data analysis are directly applicable to the BA role. Many BAs working alongside POs take this course alongside the AI for their specific role track to build a broader AI skill set across both functions.
The specific tools will evolve — but the skills this course builds are durable. Structured prompting, knowing how to frame a product problem for AI, understanding what agentic workflows are appropriate for which tasks, and being able to evaluate AI outputs critically — these are judgment skills, not button-clicking skills. The tools change; the judgment transfers. That is why the course focuses on principles and frameworks with today’s tools as the vehicle, not the destination.