Product Management

It is built for students and freshers curious about product roles at Indian startups and tech companies, engineers and analysts who already work alongside product managers and want to understand their side of the work, and anyone asked to own a feature for the first time. No previous product experience is needed. The course centres on deciding what to build and why, and on measuring whether it worked. Planning schedules and budgets is the subject of Project Management, and keeping managers, clients and other teams on side is covered in depth in Stakeholder Management.

The course uses current product practice: discovery and delivery, Jobs to be Done, problem statements, PRDs and user stories with Given-When-Then acceptance criteria, RICE, MoSCoW and the Kano model, the North Star metric and the AARRR funnel, retention cohorts, A/B tests, now-next-later roadmaps, feature flags and staged rollouts. Running examples use a food-delivery app in Indian cities, and one topic is about building for Indian users: UPI-first checkout, cash on delivery, vernacular languages, low-end Android phones and tier-2 and tier-3 cities. Tool tutorials are left out.

Every lesson is a few short reading cards built around a worked example, such as a RICE table, a funnel with conversion rates, a retention cohort or an A/B test result, with a diagram where one helps and audio narration you can listen to instead of reading. A short multiple-choice quiz follows, with an explanation for every answer, and you can ask the AI guide about any card or question. The questions ask you to make the call: which feature ranks first, which funnel step lost the most users, whether a test result is significant, or which metric should guard a launch. Every metric example shows its numbers, so you can check the arithmetic yourself. The final section compares look-alike tools, such as MoSCoW and RICE or a funnel view and a cohort view, and then works through cases such as a food-app order drop after a release and a quarterly roadmap for a fintech app.

New product managers tend to slip in the same places, and each of these has its own lesson:

• Jumping to a solution before writing down the user's problem
• Asking leading questions in user interviews and hearing what you hoped to hear
• Tracking vanity metrics such as total downloads instead of actionable ones
• Explaining a metric drop without checking seasonality, segments or an instrumentation bug
• Stopping an A/B test early because the first few days look good
• Saying yes to every one-off request from sales or a senior leader
• Treating a RICE score as the decision rather than as one input to it

Udemy and Coursera mostly teach product management through video lectures, often with an instructor walking through frameworks on slides. LinkedIn Learning offers short video courses by working professionals. This course does a different job: short narrated lessons followed by questions that make you apply a framework to numbers, rank features, read a funnel or judge an experiment. Video suits hearing how product teams work day to day, and this format builds the judgement to make product decisions quickly and back them with data. It does not include a project to build, so try each framework on an app you use every day.

Pick one app you use daily, such as a food-delivery, payments or shopping app, and keep it beside you through the course. When a lesson covers personas, Jobs to be Done or a funnel, write one for that app; when it covers RICE or MoSCoW, list three features you would add and score them. Answer each quiz question before reading its explanation, because recalling the reasoning yourself is what makes it stick. Redo the arithmetic in every metric example, since conversion rates, churn and DAU/MAU are easy to misread. Once you reach product sense cases, practise one improve-a-product case a day out loud: clarify the goal, choose a user segment, list pain points, prioritise solutions and define success metrics.