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AI Product Prototyping

Master the end-to-end journey from a vague idea to a functional AI concept and working prototype using modern low-code, prompt-based tools.

Duration40 Hours
FormatOnline, instructor-led
On completionCertificate

Course overview

This hands-on, strategic course is designed to equip Product Managers, Innovators, and Developers with the skills to translate a business problem into a validated AI product concept and quickly build a functional working prototype. You will master a rapid iteration workflow—the path from Idea → AI Concept → Working Prototype. The curriculum integrates design thinking for AI with practical application, focusing on low-code/no-code stacks (like Figma, Replit, and LLM APIs) to accelerate MVP validation and get fast, tangible results.

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Certificate of Course Completion

What you'll learn

Idea-to-Prototype Workflow

The systematic process of moving from a high-level idea to a validated, working AI prototype.

LLM-Driven Ideation

How to use tools like ChatGPT and Gemini for rapid problem solving and architectural design.

Functional Prototyping

The practical skill of building and deploying functional MVPs using low-code/no-code platforms (Replit, Bolt) and APIs.

Design Thinking for AI

Applying strategic design principles to ensure your AI solution is valuable, feasible, and user-centric.

Curriculum

5 modules · 40 Hours

01From Business Problem to AI Opportunity

- What is AI Product Prototyping: Defining the scope and objectives of AI prototyping and its role in reducing risk and speeding up iteration. - Design Thinking for AI Solutions: Applying design thinking principles to frame user problems and identify innovative, responsible AI concepts. - Translating Business Problems: Methods for taking a general business challenge and translating it into a well-defined, data-dependent AI opportunity.

02Ideation, Prompt Engineering, and User Mapping

- LLMs for Ideation: Using generative AI to accelerate brainstorming, refine features, and articulate product architecture. - Mapping User Journeys: Collaboratively mapping the user journey, identifying key AI touchpoints, and defining microinteractions. - Prompt Design for Prototype Generation: Mastering advanced prompting to generate UI code and functional logic directly.

03The Prototyping Stack: No-Code/Low-Code

Overview of Prototyping Stack: Introduction to the integrated toolkit: ChatGPT/Gemini (ideation/code snippets), Figma (design/UI integration), Make/Zapier (automation/logic), and Replit/Bolt (functional code hosting). - No-Code vs. Low-Code Approaches: Understanding when to use fully no-code UI builders versus low-code platforms for custom functional requirements.

04Building the Working Prototype

Hands-on Prototype Building: Constructing a functional prototype that demonstrates the core value of the AI concept (e.g., using Replit for live code hosting). - API Integration and Core Logic: Implementing the core AI feature by connecting model APIs (e.g., GPT, Gemini) for live, working functionality. - End-to-End Prototype Flows: Building complete, connected user flows with dynamic data to simulate a real product experience.

05Validation, Iteration, and Handoff

- User Experience (UX) for AI: Designing intuitive microinteractions and user interfaces for AI-driven features. - Rapid Idea Testing: Implementing techniques for quickly validating the prototype with users and leveraging its functional nature to get fast, actionable feedback. - Handoff and Design Systems: Integrating the prototype with design systems and preparing the documentation for a smooth handover to engineering (Product Requirement Document + Working Code).

Who it's for

Product Managers & Owners

Individuals who need to quickly validate AI concepts, reduce technical risk, and ship working prototypes faster than traditional methods.

Innovation Team Leads & Founders

Leaders focused on rapid iteration, building MVPs, and getting market feedback without deep investment in engineering time.

UX/UI Designers

Designers looking to integrate AI agents into their workflow and create functional, interactive prototypes that go beyond static mockups.

Aspiring AI Professionals

Anyone looking for a hands-on, practical bridge between business strategy and AI development.

Before you start

Familiarity with basic product development concepts, user stories, and basic API concepts is recommended. No extensive coding or deep ML knowledge is required.

How you'll learn

Immersive instructor-led sessions

Participate in dynamic, hands-on sessions led by expert instructors to gain practical skills in a supportive learning environment.

Build a functional AI Product MVP

The goal is to build a demonstrable, working prototype of an AI product feature ready for user testing and validation.

Build something real for your project portfolio

You will complete a hands-on project that can be added to your professional portfolio to demonstrate your skills to potential employers.

Learn anytime with unlimited 1-year access to contents and tools

Gain continuous learning with one year of unlimited access to all course materials, tools, and resources, allowing you to study at your own pace and revisit topics as needed.

Questions

Will I learn how to train my own AI model?

This course focuses on leveraging existing, powerful AI model APIs for speed. It is centered on application and integration, not fundamental model training.

What tools will we use?

We use cutting-edge AI prototyping tools including ChatGPT, Gemini, Figma, Make/Zapier, Replit, and the OpenAI API.

Is this course for beginners?

It’s suitable for those with some technical or product background, but it’s an ideal entry point for hands-on AI product development.

Is there certification upon completion?

Yes, upon successful completion, participants will receive a certificate demonstrating their competency in AI product prototyping.

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