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Certificate in AI Product Development and Innovation

Design, prototype, and validate AI-enabled digital products while applying innovation and product management principles.

Last updated 07/2026EnglishIntermediate

About this programme

Design, prototype, and validate AI-enabled digital products while applying innovation and product management principles.

Delivered as 60 live two-hour sessions across 8 modules, with a graded build at the end of every module and a mentor-reviewed capstone to finish.

Course outcomes

What you will be able to do on completion

This programme is built around capability, not coverage. By the end you will be able to:

01Frame a product problem before reaching for an AI solution
02Judge which problems AI genuinely solves and which it does not
03Run discovery research and translate findings into product decisions
04Prototype an AI-enabled product quickly enough to test it
05Design for uncertainty — confidence, error states and user trust
06Define metrics that show whether an AI feature is working
07Run experiments and interpret results honestly
08Build a roadmap and business case for an AI product
09Pitch a validated AI product concept with evidence behind it

Course content

8 modules · 60 sessions · 120 hours

Sessions run two hours each, live with an instructor. Each module closes with a graded build.

1.1 What makes an AI product differentPreview2 hrs

1.2 Outcomes over featuresPreview2 hrs

1.3 The AI product lifecycle2 hrs

1.4 Roles in an AI product team2 hrs

1.5 Opportunity and risk in AI products2 hrs

1.6 Case studies: successes and failures2 hrs

1.7 Ethics as a product constraint2 hrs

1.8 Setting up your product toolkit2 hrs

2.1 Finding problems worth solving2 hrs

2.2 Interviewing users well2 hrs

2.3 Jobs to be done for AI products2 hrs

2.4 Mapping the current experience2 hrs

2.5 Synthesising research into insight2 hrs

2.6 Writing sharp problem statements2 hrs

2.7 Prioritisation frameworks2 hrs

2.8 Sizing the opportunity2 hrs

2.9 Aligning stakeholders2 hrs

2.10 Workshop: framing your product problem2 hrs

3.1 What current models can and cannot do2 hrs

3.2 Matching capability to problem2 hrs

3.3 Data availability and readiness2 hrs

3.4 Build, buy or fine-tune2 hrs

3.5 Cost and latency as design constraints2 hrs

3.6 Technical risk assessment2 hrs

3.7 Working with engineers and data scientists2 hrs

3.8 Feasibility review of your concept2 hrs

4.1 Prototyping fidelity and when to use it2 hrs

4.2 Wizard-of-Oz and concierge testing2 hrs

4.3 No-code and low-code AI prototypes2 hrs

4.4 Designing the prompt as an interface2 hrs

4.5 Interaction patterns for AI features2 hrs

4.6 Designing for confidence and uncertainty2 hrs

4.7 Error, empty and edge states2 hrs

4.8 Onboarding and expectation setting2 hrs

4.9 Usability testing an AI prototype2 hrs

4.10 Project: a testable AI prototype2 hrs

5.1 Choosing product metrics that matter2 hrs

5.2 Leading versus lagging indicators2 hrs

5.3 Measuring AI quality alongside usage2 hrs

5.4 Designing an experiment2 hrs

5.5 A/B testing with probabilistic output2 hrs

5.6 Reading results without fooling yourself2 hrs

5.7 Qualitative signals and user feedback2 hrs

5.8 Deciding to persevere or pivot2 hrs

5.9 Building a validation plan2 hrs

5.10 Project: validating your concept2 hrs

6.1 Bias and fairness in product decisions2 hrs

6.2 Transparency and explainability2 hrs

6.3 Privacy and data minimisation2 hrs

6.4 Consent, control and user agency2 hrs

6.5 Failure disclosure and recovery2 hrs

6.6 Responsible AI review of your product2 hrs

7.1 Building an AI product roadmap2 hrs

7.2 Pricing and value capture2 hrs

7.3 Cost modelling for AI features2 hrs

7.4 Go-to-market for AI products2 hrs

7.5 Launch, feedback loops and iteration2 hrs

7.6 Pitching to stakeholders2 hrs

8.1 Capstone pitch and mentor review2 hrs

8.2 Portfolio, resume and interview preparation2 hrs

Requirements

A laptop with internet access
Willingness to work through hands-on builds each module
No prior AI background required — the first module starts from fundamentals
Around four hours a week outside sessions for project work

Description

Design, prototype, and validate AI-enabled digital products while applying innovation and product management principles.
60 live sessions across 8 modules, 120 hours in total.
Every module closes with a graded build reviewed by a mentor.
Finish with a verifiable certificate recognised by our hiring partners.

Instructor

Dr. Neha Rao

Lead AI Instructor · TEVVO Academy

12,480 reviews41,200 students9 courses

Neha has spent a decade building machine learning systems in production, most recently leading an applied AI team. She teaches the way she works — starting from a real problem, then building the smallest thing that solves it.

Student feedback

4.9Course rating

78%

14%

Featured reviews

Ananya S.

Structured, practical and paced properly. The graded build at the end of each module is what made it stick.

Karthik R.

The mentor reviews were the most valuable part — real feedback on real work, not just a quiz score.

Meera J.

Genuinely current material and a sensible schedule alongside a full-time job.