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Certificate in AI for Engineering Design and Innovation

Apply AI tools to engineering design, simulation, problem-solving, prototyping, technical documentation, and innovation across multiple engineering disciplines.

Last updated 07/2026EnglishIntermediate

About this programme

Apply AI tools to engineering design, simulation, problem-solving, prototyping, technical documentation, and innovation across multiple engineering disciplines.

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:

01Apply AI tools across the engineering design cycle
02Use generative design to explore options a human would not reach
03Set up and interpret AI-accelerated simulation
04Prototype and iterate faster without losing engineering rigour
05Produce technical documentation with AI assistance and proper review
06Apply structured innovation methods to engineering problems
07Judge when an AI-generated design must be verified by hand
08Work across disciplines on a shared engineering problem
09Deliver a validated design project with documented reasoning

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 AI changes in engineering practicePreview2 hrs

1.2 Models, data and their limitsPreview2 hrs

1.3 Where AI belongs in the design cycle2 hrs

1.4 Engineering data and formats2 hrs

1.5 Verification as a non-negotiable2 hrs

1.6 Tooling landscape for engineers2 hrs

1.7 Ethics and liability in AI-assisted design2 hrs

1.8 Setting up your design workspace2 hrs

2.1 Principles of generative design2 hrs

2.2 Defining constraints and objectives2 hrs

2.3 Topology optimisation basics2 hrs

2.4 Exploring a design space2 hrs

2.5 Multi-objective trade-offs2 hrs

2.6 Material and manufacturing constraints2 hrs

2.7 Interpreting generated geometry2 hrs

2.8 Design for manufacture checks2 hrs

2.9 Comparing generated and conventional designs2 hrs

2.10 Project: a generatively designed part2 hrs

3.1 Simulation fundamentals refresher2 hrs

3.2 Surrogate models and why they help2 hrs

3.3 Setting up an AI-accelerated study2 hrs

3.4 Mesh, boundary and setup pitfalls2 hrs

3.5 Interpreting simulation output2 hrs

3.6 Validating a surrogate against ground truth2 hrs

3.7 Uncertainty in simulation results2 hrs

3.8 Build: an accelerated analysis workflow2 hrs

4.1 From concept to testable prototype2 hrs

4.2 Rapid prototyping methods2 hrs

4.3 AI in CAD workflows2 hrs

4.4 Parametric and script-driven modelling2 hrs

4.5 Test planning and instrumentation2 hrs

4.6 Capturing and analysing test data2 hrs

4.7 Iterating on evidence2 hrs

4.8 Failure analysis2 hrs

4.9 Cost and time trade-offs2 hrs

4.10 Project: a prototype and test report2 hrs

5.1 Technical writing standards2 hrs

5.2 Drafting specifications with AI assistance2 hrs

5.3 Reviewing AI-drafted technical content2 hrs

5.4 Extracting knowledge from standards and manuals2 hrs

5.5 Building a searchable engineering knowledge base2 hrs

5.6 Drawing and BOM documentation2 hrs

5.7 Traceability and revision control2 hrs

5.8 Reporting results clearly2 hrs

5.9 Handover and maintainability2 hrs

5.10 Project: a complete design dossier2 hrs

6.1 Structured problem-solving methods2 hrs

6.2 Systematic inventive thinking2 hrs

6.3 Cross-disciplinary design reviews2 hrs

6.4 Concept selection frameworks2 hrs

6.5 Managing technical risk in innovation2 hrs

6.6 Workshop: a cross-discipline challenge2 hrs

7.1 Design verification and validation2 hrs

7.2 Relevant standards and compliance2 hrs

7.3 Safety factors and failure modes2 hrs

7.4 Documentation for audit2 hrs

7.5 Sustainability considerations2 hrs

7.6 Final design review2 hrs

8.1 Capstone design 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

Apply AI tools to engineering design, simulation, problem-solving, prototyping, technical documentation, and innovation across multiple engineering disciplines.
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.