First year business students, final year students and new graduates preparing for assessed work, placements and early career recruitment.
AI Fluency for Early Career Professionals
Using AI is not the same as knowing how to judge it or what remains your responsibility when it drafts first. This course builds lasting working habits for assignments, group projects, placements, applications and early career work. It teaches Delegation, Description, Discernment and Diligence without relying on tool tutorials. The scenarios begin at university and extend to workflows, policy, money and risk as responsibility grows.
A practical course run by Rushi Vyas, in person or online: 3 stages, 27 teaching screens, and verifiable Open Badges issued after each session. The interactive courseware on this page opens with the access code shared with your cohort.
Who this course suits
- Level 1, AI-Ready Professional, for a student doing their own assignments and applications and asking what stays their responsibility when AI drafts first
- Level 2, AI-Enabled Professional, for a student whose work other people rely on: a group project, a placement supervisor, a part-time job with customers
- Level 3, AI-Accelerated Professional, for a student setting the rules for others: a society with a budget, a case competition team, a graduate intake
AI-Ready Professional
First year students, final year students and new graduates responsible for their own assignments, applications, study and early career output.
Build sound judgement and working habits for your own study, applications and early career work.
Questions this level answers:
- What should be handed to AI when an assignment still has to show your own thinking?
- How can a brief make an AI draft easier to check?
- When does AI assistance need to be disclosed?
Own the work
Delegation and Diligence: decide what stays with you, then keep responsibility for anything that leaves your name.
- Fluency is judgement, not tool familiarity
- Your name stays on the work
- Assist, delegate or keep
- Know when to keep the work
- Module summary
Brief, check and disclose
Description, Discernment and Diligence: give a bounded brief, check by consequence, and record AI use honestly.
- A brief that makes checking possible
- Check more where the consequence is higher
- Keep an honest record
- Level summary
AI-Enabled Professional
Students and new graduates coordinating a group project, placement workflow or customer task where other people rely on their output and review.
Build consistent review and handover habits when a shared workflow depends on AI-assisted work.
Questions this level answers:
- How do group members use AI consistently without pretending they worked the same way?
- Which review depth fits a shared deliverable when time is limited?
- Where should the record of AI-assisted work sit before a supervisor relies on it?
Coordinate the shared workflow
Delegation and Description: set one contribution standard, make handoffs reviewable, and name the final owner.
- When other people rely on the output
- One brief for many contributors
- Build a handoff that can be reviewed
- Review without redoing the whole task
- Module summary
Review before others rely
Discernment and Diligence: set review depth by consequence, retain the evidence, and raise decisions outside your scope.
- Review depth follows consequence
- Customer-facing work gets a human read
- Keep the record and raise what exceeds your scope
- Level summary
AI-Accelerated Professional
Society presidents, case competition leads, graduate intake representatives and early founders who set rules for others and own budget, policy, contracts, spend and risk.
Set the policy, risk appetite and mandate for AI use when budget, spend, vendor choices and other people's work sit under your name.
Questions this level answers:
- What must a working AI policy say before a committee starts using it?
- Which vendor claims need evidence before a licence is approved?
- Who owns the decision when AI spend competes with another budget priority?
Set the operating rules
Diligence and Discernment: set policy, risk appetite, decision rights and evidence for other people's AI use.
- When the rules sit under your name
- Write a one-page working policy
- Set risk appetite before pressure arrives
- Appoint owners and design escalation
- Module summary
Make defensible commercial choices
Discernment, Diligence and Delegation: fund capability, test vendor claims, negotiate terms and show the board decision evidence.
- Fund the right capability
- Test the vendor and the contract
- Show the board evidence, not confidence
- Level summary
Credential
Each level ends in a scenario check and is recognised with a verifiable Open Badge: Foundation, then Practitioner, then Leader. Skill badges are earned by case study, and completing three courses earns the Cross-Industry badge.
Common questions
Is this course for first years only?
It is written for first years and reads just as well for a final year or a new graduate in a first job. The scenarios are student shaped; the judgement is the same one a workplace expects.
Does it teach a particular AI tool?
No. Tools change every term. The course teaches what to hand to AI, how to brief it, how to check what comes back and when to say no, and it names no products.
What does a student receive?
A verifiable Open Badge for each level passed, with its own hosted verification page and a one-click add to LinkedIn, issued by a person after the check.
Taught by Rushi Vyas, AI trainer and keynote speaker. About Rushi