Aleph Applied AI Academy
Practical AI training for disciplined, human-directed work.
Aleph Applied AI Academy teaches practical AI workflows, verification habits, privacy-aware prompting, documentation discipline, and human-directed automation for real work.
Core principle
The Academy does not teach people to chase AI hype. It teaches people to build governed workflows: define the task, protect sensitive information, verify outputs, document decisions, and keep humans responsible.
The public outline currently shows the foundation modules. The planned membership model expands this into a year-long cadence of twelve recorded classes and twelve live sessions. Enrollment, scheduling, pricing, and protected delivery are still being prepared.
What you will learn
Six habits that make AI use accountable.
Prompt with purpose
Define the task before touching the tool. Write prompts that state the goal, the constraints, and the format the work actually needs.
Protect private information
Know what never goes into a prompt: client data, credentials, health and financial details, and anything you are not authorized to share.
Verify claims and sources
Treat AI output as a draft, not an answer. Check citations, test claims, and know when a confident answer is wrong.
Build repeatable workflows
Turn one-off wins into documented, repeatable processes that anyone on your team can run the same way twice.
Document decisions and handoffs
Record what the AI did, what a human decided, and why — so the work survives audits, handoffs, and your own memory.
Keep human approval in the loop
Design automation where a person owns every consequential decision. The tool drafts; a human approves.
What you will build
Working artifacts, not certificates of attendance.
Every learner leaves with a set of documents and tools built for their own work — the same artifacts submitted for Applied Portfolio Review.
Personal AI use policy
A one-page policy stating what you use AI for, what you never use it for, and who is responsible for output.
Safe prompting checklist
A pre-flight check you run before any prompt that touches real work or real people.
Verification checklist
A repeatable routine for checking facts, sources, numbers, and quotes before AI-assisted work ships.
Reusable prompt library
A curated set of prompts for your actual recurring tasks — tested, annotated, and yours.
Workflow map
A diagram of one real process showing where AI assists, where humans decide, and where output gets checked.
AI-assisted SOP
A standard operating procedure for one recurring task, written so a teammate could run it tomorrow.
Project handoff document
A handoff template that captures context, decisions, and open questions when AI-assisted work changes hands.
Final applied portfolio
The collected artifacts above, applied to your own work, submitted for Applied Portfolio Review.
Training path
Eight modules, from orientation to launch.
- Module 1
Orientation: AI as a tool under human authority
What these tools are, what they are not, and why the person — not the model — owns every decision.
- Module 2
Prompting for useful work
Task definition, context setting, output formats, and iteration habits that produce usable drafts.
- Module 3
Verification, citations, and source discipline
Fact-checking routines, source tracing, and recognizing fluent nonsense before it costs you.
- Module 4
Privacy, boundaries, and sensitive information
Data classification for everyday users: what is safe to share, what is not, and how to work around the gap.
- Module 5
Workflow mapping and SOP creation
Mapping a real process end to end, then writing the SOP that makes it repeatable.
- Module 6
Automation with human approval
Where automation helps, where it quietly creates risk, and how to keep an accountable person in the loop.
- Module 7
Applied portfolio build
Assembling your policy, checklists, prompt library, workflow map, and final project into a working portfolio.
- Module 8
Review, correction, and launch plan
Portfolio review feedback, corrections, and a concrete plan for using what you built in real work.
Academy tracks
Choose the track that fits how you work.
Same curriculum and portfolio standard across every track — the difference is who learns alongside you and what your organization needs documented.
Basic
Core program · planned
Price pending
A practical starting point for learners who want grounded AI fluency, safe prompting, and useful work habits.
- Core learning path
- Verification and privacy habits
- Applied Portfolio Review
Advanced
Deeper program · planned
Price pending
For learners ready to connect AI to workflows, repositories, automation, and real projects.
- Basic plus deeper content
- Workflow and automation practice
- Additional project guidance
ML Engineer
Advanced systems · planned
Quote-based
For learners pursuing deeper system design, data workflows, agents, and complete AI ecosystems.
- Advanced systems architecture
- Agent and data workflow concepts
- Guided ecosystem project
Online enrollment and payment access are being prepared. For now, request Academy access and we will follow up with the current enrollment path.
When checkout opens, payments will be processed by Stripe or PayPal — card details are never stored by UVP. Track pricing is set in the product admin before launch.
Applied Portfolio Review
Proof of practice, honestly framed.
Learners submit a small portfolio of practical artifacts. The review confirms applied participation and responsible workflow practice.
Portfolio artifacts
- AI-use policy
- Verification checklist
- Prompt library sample
- Workflow / SOP map
- Final applied project
What the review is — and is not
The Applied Portfolio Review confirms that you did the work and practiced responsible, human-directed AI workflows. It is not formal accreditation, academic credit, licensure, or employment certification, and it carries no income or employment guarantee.
Completion of the applied portfolio review may help demonstrate familiarity with UVP’s standards and workflows. If UVP later opens contributor, contractor, or employment opportunities, academy participation may be considered as one factor in review. Completion does not guarantee employment, paid work, contracting opportunities, income, or placement.
Why Aleph Academy is different
Most AI training fails in one of four ways.
Hype-driven AI content
teaches speed without responsibility.
Generic prompt lists
teach tricks without workflow discipline.
Enterprise AI strategy
often ignores small-business reality.
Unmanaged automation
creates risk when nobody owns the decision.
Aleph Applied AI Academy trains people to use AI inside clear boundaries: purpose, privacy, verification, documentation, and human approval.
FAQ
Questions, answered plainly.
Who is this for?
Individuals, families, teams, ministries, nonprofits, and small businesses that want to use AI for real work without surrendering human judgment. No prior AI experience is assumed.
Is this only for Christians?
No. The core curriculum is built for anyone who wants accountable, human-directed AI use. An optional Christian stewardship track is available for learners and organizations that want faith-framed discussion alongside the same practical material — it is optional, and skipping it removes nothing from the core training.
Do I need technical experience?
No. The Academy assumes you can use a web browser and the everyday tools of your work. Everything else is taught in plain language, and the focus is on judgment and workflow — not code.
Will sessions be recorded?
Live sessions are planned to be recorded and made available to enrolled learners so you can catch up on your own schedule. Recording details for each cohort are confirmed at enrollment.
How does the Applied Portfolio Review work?
You submit a small portfolio of practical artifacts — your AI-use policy, verification checklist, prompt library sample, workflow/SOP map, and final applied project. A reviewer confirms applied participation and responsible workflow practice and returns feedback with any needed corrections.
Is this formal accreditation?
No. The Applied Portfolio Review confirms applied participation and responsible workflow practice. It is not formal accreditation, academic credit, licensure, or employment certification, and it does not guarantee income or employment outcomes.
Can teams or households learn together?
The public track model is currently Basic, Advanced, and ML Engineer. Team and household enrollment options may be added as the Academy portal and support model are finalized. Contact UVP if you want to discuss a group learning need.
How do cancellation and refunds work?
Paid access may be cancelled according to the plan terms shown at checkout. Refund eligibility is governed by the Refund Policy linked in the footer. Until live checkout is enabled, purchase buttons may operate in request-only or test mode.
Ready to build governed AI workflows?
Request access and UVP will follow up with track availability, schedule, and pricing.