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Minimum Viable Product (MVP) Course
More than 2 million students worldwide

Minimum Viable Product (MVP) Course

Stop building products nobody wants. This course gives you a proven, step-by-step system for validating your idea before you invest serious time or money. From customer discovery to experiment design to pivot decisions, you'll master the full MVP lifecycle and launch with confidence backed by real evidence.

Dedika for businesses

What you will learn:

  • Apply lean startup principles to reduce waste and accelerate validated market learning.

  • Design structured customer discovery interviews that uncover genuine, high-priority pain points.

  • Select the right MVP format — concierge, landing page, prototype, and more — for each hypothesis.

  • Build and execute a complete experiment plan with clear success thresholds and decision rules.

  • Analyze quantitative and qualitative MVP data to produce an evidence-based learning report.

  • Translate validated MVP insights into a prioritized product roadmap ready for scaling.

How you study in practice Minimum Viable Product (MVP) Course

How you practise Minimum Viable Product (MVP) Course

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Course content

8 Chapters • 38 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

MVP Fundamentals and Startup Thinking

  • Lesson 1 • The Role of Assumptions in Products

    Teaches how untested assumptions drive product failure and how surfacing them early is critical. Links assumption mapping directly to MVP scope decisions.

  • Lesson 2 • What an MVP Actually Is

    Defines MVP precisely, contrasting it with prototypes, pilots, and full products. Grounds the chapter by eliminating common misconceptions before deeper concepts are introduced.

  • Lesson 3 • Defining Success for an MVP

    Establishes how success metrics differ between an MVP and a mature product. Students learn to set measurable learning goals before building anything.

  • Lesson 4 • Lean Startup Core Principles

    Introduces build-measure-learn cycles and validated learning as the engine of MVP development. Connects lean thinking to reduced waste and faster market feedback.

Chapter 2See details

Problem Discovery and Customer Research

  • Lesson 1 • Identifying Target Customer Segments

    Covers segmentation frameworks to pinpoint who experiences the problem most acutely. Accurate segmentation prevents building for a market that does not exist.

  • Lesson 2 • Secondary Research and Market Signals

    Supplements interviews with desk research, trend data, and competitor analysis to confirm problem scale. Teaches students to triangulate qualitative and quantitative signals.

  • Lesson 3 • Conducting Customer Discovery Interviews

    Teaches structured interview techniques that surface genuine pain points without leading respondents. Directly feeds the problem validation work in later sections.

  • Lesson 4 • Validating the Problem Statement

    Synthesises research into a concise, testable problem statement with supporting evidence. A validated problem statement is the prerequisite for all solution work ahead.

  • Lesson 5 • Mapping Customer Jobs and Pain Points

    Applies jobs-to-be-done theory to translate raw interview data into structured problem maps. Reveals which pains are severe enough to motivate behaviour change.

Chapter 3See details

Solution Ideation and Concept Definition

  • Lesson 1 • Evaluating and Selecting Solution Concepts

    Applies convergent thinking tools such as impact-effort matrices and dot voting to select the strongest concept. Connects selection criteria back to validated customer pains.

  • Lesson 2 • Scoping the MVP Feature Set

    Applies ruthless prioritisation to reduce the concept to its smallest testable form. Students practice cutting features without losing the core value hypothesis.

  • Lesson 3 • Ideation Frameworks and Techniques

    Introduces divergent thinking methods including how-might-we prompts, brainwriting, and analogical reasoning. Generates a broad solution space before narrowing begins.

  • Lesson 4 • Defining the Value Proposition

    Crafts a precise value proposition that links the solution to specific customer jobs and pains. A sharp value proposition guides every subsequent scoping and design decision.

Chapter 4See details

MVP Types and Experiment Design

  • Lesson 1 • Taxonomy of MVP Types

    Catalogs concierge, Wizard of Oz, landing page, explainer video, and prototype MVPs with real examples. Establishes a shared vocabulary for selecting the right format.

  • Lesson 2 • Matching MVP Type to Hypothesis

    Provides a decision framework for selecting the MVP format that tests the riskiest assumption fastest. Prevents over-engineering by aligning format to the specific learning goal.

  • Lesson 3 • Ethical Considerations in MVP Testing

    Addresses informed consent, data privacy, and honest representation when testing with real users. Ethical practices protect participants and preserve brand trust during experiments.

  • Lesson 4 • Writing Testable Hypotheses

    Structures assumptions as falsifiable if-then hypotheses with explicit success criteria. Rigorous hypothesis writing prevents ambiguous results that cannot drive decisions.

  • Lesson 5 • Designing the Experiment Plan

    Builds a complete experiment plan covering method, sample, timeline, and decision rules. The plan becomes the operational blueprint for building and running the MVP.

Chapter 5See details

Building the MVP: Execution Fundamentals

  • Lesson 1 • No-Code and Low-Code Build Options

    Surveys no-code and low-code platforms suited to rapid MVP construction across product categories. Empowers non-engineers to build testable artifacts without development resources.

  • Lesson 2 • Managing Scope Creep During Build

    Identifies triggers of scope creep and provides techniques to maintain MVP discipline under pressure. Scope control directly determines whether the MVP remains minimum and testable.

  • Lesson 3 • Agile and Sprint-Based MVP Development

    Introduces sprint planning, backlog management, and daily standups adapted for MVP-scale teams. Keeps build cycles short and focused on the minimum needed for the experiment.

  • Lesson 4 • Rapid Prototyping Techniques

    Covers paper prototyping, clickable wireframes, and interactive mockups as fast build methods. Connects prototype fidelity levels to the validation questions being tested.

  • Lesson 5 • Quality Thresholds for MVP Release

    Defines the minimum quality bar an MVP must meet to generate valid, trustworthy data. Distinguishes acceptable MVP roughness from defects that corrupt experiment results.

Chapter 6See details

Measuring Results and Analyzing Data

  • Lesson 1 • Producing the Learning Report

    Structures findings into a concise learning report that connects evidence to hypotheses and decisions. The report becomes the artifact that justifies the next strategic move.

  • Lesson 2 • Synthesising Qualitative Feedback

    Uses affinity mapping and thematic coding to extract patterns from interview and survey responses. Qualitative synthesis reveals the why behind quantitative behavioural data.

  • Lesson 3 • Collecting Behavioral and Attitudinal Data

    Covers analytics instrumentation, session recording, surveys, and follow-up interviews as data sources. Combines behavioural evidence with attitudinal data for a complete picture.

  • Lesson 4 • Defining and Tracking Key Metrics

    Establishes which quantitative and qualitative metrics align with each hypothesis type. Metric selection before launch prevents post-hoc rationalisation of ambiguous results.

  • Lesson 5 • Analyzing Quantitative MVP Data

    Applies basic statistical reasoning, cohort analysis, and funnel analysis to MVP result sets. Teaches students to distinguish signal from noise in small-sample MVP data.

Chapter 7See details

Pivot, Persevere, or Stop Decisions

  • Lesson 1 • Knowing When to Stop

    Establishes objective criteria for discontinuing an MVP effort and redirecting resources. Stopping gracefully is a strategic skill that preserves team capacity for better opportunities.

  • Lesson 2 • Types of Pivots and When to Use Them

    Catalogs zoom-in, zoom-out, customer segment, and business model pivots with decision triggers. Matching pivot type to the specific failed assumption prevents misdirected changes.

  • Lesson 3 • Interpreting Results Against Hypotheses

    Teaches systematic comparison of actual results to pre-set success thresholds. Prevents emotional or political bias from overriding evidence-based conclusions.

  • Lesson 4 • Persevere Criteria and Iteration Planning

    Defines what constitutes sufficient validation to continue and how to plan the next build cycle. Persevere decisions must be paired with a concrete improvement hypothesis.

  • Lesson 5 • Communicating Decisions to Stakeholders

    Provides frameworks for presenting pivot, persevere, or stop decisions to investors, executives, and teams. Clear communication maintains trust and secures resources for the next cycle.

Chapter 8See details

Scaling from MVP to Full Product

  • Lesson 1 • Transitioning from MVP to Engineering Scale

    Addresses technical debt, architecture decisions, and team structure changes required for scale. Students learn when to rebuild vs. extend the MVP codebase or toolset.

  • Lesson 2 • Go-to-Market Strategy for Scaled Launch

    Designs a go-to-market plan that leverages MVP learnings about channels, messaging, and segments. Validated customer insights directly inform acquisition and positioning strategy.

  • Lesson 3 • Sustaining a Learning Culture Post-MVP

    Embeds continuous experimentation and customer feedback loops into the scaled product organisation. Prevents the loss of MVP discipline as teams and processes grow larger.

  • Lesson 4 • Building the Product Roadmap

    Translates validated MVP learnings into a prioritised, outcome-based product roadmap. The roadmap balances customer needs, business goals, and technical feasibility.

  • Lesson 5 • Signals That Indicate MVP Readiness to Scale

    Identifies retention, referral, and revenue signals that confirm product-market fit before scaling. Premature scaling without these signals is a leading cause of startup failure.

Certification

Your valid completion certificate

This course is for you:

  • First-time founders: eager to test ideas without wasting resources.

  • Product managers: ready to champion evidence-driven decisions at work.

  • Freelance designers: wanting to offer clients full product go-to-market strategy value.

  • Career changers: transitioning into product roles from unrelated industries.

  • Side-project builders: tired of shipping features nobody actually uses.

  • Early-stage startup employees: needing structured methods to reduce launch risk.

What our students say

Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to change platforms... I'm grateful for everything you do, I've already recommended you to other people...
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Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
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Mariana FerresPhotography Student
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The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
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André FelipePrompt Engineering Student

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