Bootcamp

FDE Financial AI Bootcamp

Learn financial AI requirements analysis, pricing, deployment, acceptance, and delivery SOPs through real project practice.

Project practice
Delivery SOP
Acceptance oriented
6
Training modules
From demand to operations
P
Practice first
Scenario tasks and deliverables
0
Licence implication
Training is not regulated advice
1
Portfolio project
Use a realistic but non-client scenario
Modules

What the bootcamp trains

Participants work through project scoping, pricing, deployment design, governance, and acceptance with realistic financial scenarios.

Demand analysis

Turn a broad AI request into scope, data assumptions, user roles, and measurable outcomes.

Question list
Scenario score

Solution and pricing

Prepare a simple deployment proposal, milestone plan, cost logic, and acceptance scope.

Proposal structure
Budget bands

Deployment build

Design knowledge-base setup, AI employee roles, workflow templates, and review paths.

Knowledge-base plan
Prompt templates

Acceptance and operations

Create training notes, usage reports, issue logs, optimization rhythm, and handoff materials.

Acceptance checklist
Monthly report
Bootcamp Flow

A project-style route from brief to handoff

The bootcamp does not claim client delivery experience. It uses realistic, non-client exercises to train project judgement.

01

Receive scenario brief

02

Scope and price project

03

Build deployment plan

04

Present acceptance pack

Next Step

After the bootcamp

Move from practice to certification context, engineer membership, or a real deployment request.

FDE-Finance Certification

Review capability assessment scope.

Open

Engineer membership

Understand practitioner profile requirements.

Open

Submit deployment request

Turn a company scenario into a qualified lead.

Open
Enterprise Procurement Route

Start with non-sensitive context, then move into an accepted AI deployment route

FDE.HK connects intake, diagnosis, solution design, delivery, and managed operations into one enterprise buying path for business, technology, compliance, and management teams.

Non-sensitive first
Sensitive materials wait until NDA, permission, and data boundaries are confirmed
Diagnose before build
Clarify scenarios, users, data, budget, and acceptance criteria first
Accepted delivery
Plans, workflows, training, operations, and acceptance checklists stay traceable