
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.
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
For companies looking to train their teams
With Dedika for businesses, the course includes exercises and examples tailored to your company and its specific needs.
Course content
8 Chapters • 38 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsMVP Fundamentals and Startup Thinking
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 2HideHide detailsSee detailsProblem Discovery and Customer Research
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 3HideHide detailsSee detailsSolution Ideation and Concept Definition
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 4HideHide detailsSee detailsMVP Types and Experiment Design
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 5HideHide detailsSee detailsBuilding the MVP: Execution Fundamentals
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 6HideHide detailsSee detailsMeasuring Results and Analyzing Data
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 7HideHide detailsSee detailsPivot, Persevere, or Stop Decisions
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 8HideHide detailsSee detailsScaling from MVP to Full Product
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.
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.
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