AI for People & Operations

What you’ll be able to do

The job, task by task.

1. 1Score 200 applications against a written rubric. Cut a shortlist of 30. Then check whether your shortlist looks like the applicant pool before it leaves your desk
2. 2Turn a 140-row candidate sheet carrying PAN, UAN, date of birth and current CTC into something you can safely paste into an AI tool. Keep the key that maps it back
3. 3Draft a job description that matches the approved requisition. Then work Naukri Resdex and LinkedIn until 40 candidates have actually replied, not until 400 have been messaged
4. 4Build a week of interview slots for 25 candidates across four panels. Then run the no-show recovery loop when six of them do not turn up on day one
5. 5Match a month of biometric punches against the leave register before the payroll cut-off. Clear the exception queue. Hand payroll a loss-of-pay figure that survives being checked
6. 6Rewrite the one-line consent tick box into a plain-language notice with one specific purpose. Then answer a rejected candidate who has asked you to delete everything you hold on her
7. 7Answer a Monday morning queue of 30 employee helpdesk tickets from the policy handbook. Pull out the ones AI answered confidently that you are not allowed to answer at all
8. 8Sort your own job into what AI does, what it must not touch and what it has made new — and brief it so it stops guessing.
9. 9Trace every claim and number an AI gives you back to a source, make it write the formula rather than the answer, and keep a work log a manager accepts.
10. 10Find the personal data already on your desk, substitute before you paste, and know when a tool may not touch a file at all.
11. 11Draft, cut and translate without sounding like a machine, turn a broken export into a pivot, and hand over a prompt library your team can use.

• Excel
• Google Sheets
• Naukri
• GreytHR
• Google Docs

Syllabus

Eight weeks, one desk at a time.

Weeks 1-4 are the AICP common core, shared by every profession track: sixteen lessons on what AI does at a desk, how to verify it, and how to keep personal data out of it. Already finished one profession? The core carries over.

1. Week 1

   Week 1 · What AI does at your desk

   Shared core

   1. Three columns on a real job advertisement

      Take the job advertisement you actually applied to and sort every duty in it into three columns - AI does it, AI must not touch it, AI has made this new work

      • JD_recruitment_coordinator_sundaram.pdf.md
      • branch_reality_note.txt
      planted error 22 min

   2. The context pack that makes a prompt work

      Build a five-part context pack for one real task at your desk. Run the same prompt twice - once naked, once with the pack. Then show your manager the difference

      • campaign_tracker.xlsx
      • client_constraints.txt
      • two_past_emails.pdf.md
      planted error 23 min 3 min

   3. Argue the first draft down to something usable

      Get a first draft out of the AI in one shot. Then critique it, constrain it and regenerate. Stop when a dealer would read it without asking you a question

      • dealer_scheme_note.txt
      • last_year_circular.pdf.md
      • product_master_oct.xlsx
      planted error 22 min

   4. The five things it will get wrong every time

      Run five live prompts at your own desk. Find the five failure classes AI is reliably wrong about. Write the one-line check that catches each one

      • compliance_circular_nov2025.pdf.md
      • five_prompt_worksheet.csv
      • tool_pricing_screenshot.png.md
      planted error 23 min 3 min
2. Week 2

   Week 2 · Verify everything

   Shared core

   1. Every claim traced back to a source

      Take an AI-written summary note. Trace every factual claim in it to a page in the source pack. Hand over the claims log that proves you checked each one

      • ai_draft_briefing_note.docx.md
      • client_brand_guidelines.pdf.md
      • master_services_agreement.pdf.md
      planted error 22 min

   2. Make the AI write the formula, not the answer

      Get a correct total out of a 412-row expense export. Do not let the model do any arithmetic

      • oct_reimbursements.csv
      planted error 22 min 3 min

   3. Ten outputs, one drill, count what you catch

      Work through ten AI outputs on the clock, mark each one clean or defective, name the defect, and score yourself against the answer key

      • answer_key.pdf.md
      • catch_drill_ten_outputs.pdf.md
      • source_pack_for_drill.xlsx
      planted error 23 min

   4. The work log a manager will accept

      Write the AI work log for one week of your own tasks. A manager or an auditor should be able to rebuild what the tool did. Also what you checked, and what you signed off

      • ca_request_email.pdf.md
      • chat_history_export.txt
      • finance_signoff_sheet.pdf.md
      planted error 24 min 3 min
3. Week 3

   Week 3 · Personal data and disclosure

   Shared core

   1. Find the personal data already sitting in your shared folder

      Go through one shared-drive folder. Mark every file that holds personal data. Use the DPDP Act 2023 and the Rules notified 14 Nov 2025

      • dpdp_plain_extract.pdf.md
      • ops_folder_index.csv
      • vendor_master.xlsx
      planted error 22 min

   2. Build the substitution sheet before you paste anything

      Build a substitution sheet and use it. Then you can send a 60-row grievance list to an AI tool without exposing a single person

      • grievances_q2.csv
      • substitution_sheet_template.xlsx
      planted error 23 min 3 min

   3. Five situations, one question - may this tool touch this file at all

      For five real work situations, decide whether a consumer AI tool may be used at all. Write the one-line reason you would give your manager

      • ai_data_controls_screen.png.txt
      • five_situations.docx.md
      • trishul_it_policy_feb.pdf.md
      planted error 21 min

   4. Say the AI wrote it, and never let it decide about a person

      Decide which of six deliverables must carry an AI disclosure. Then reject an AI shortlist that ranks people while calling itself neutral

      • ai_shortlist_output.docx.md
      • applicant_summary.csv
      • intern_jd.pdf.md
      • six_deliverables_list.docx.md
      planted error 23 min 3 min
4. Week 4

   Week 4 · Writing, data and handover

   Shared core

   1. Draft it, cut it, then make the Hindi sound like a person wrote it

      Restructure a customer notice. Summarise it in five lines. Translate it into Hindi. Then fix the three places the output goes stilted

      • branch_call_script_old.docx.md
      • customer_language_split.csv
      • fee_notice_legal_draft.pdf.md
      planted error 22 min

   2. From a broken export to a pivot your manager can read out

      Turn a 1,240-line sales export into a clean table and a region pivot. Then get the single average-order-value figure your manager asked for

      • q2_sales_export.csv
      • zenpack_price_policy.pdf.md
      planted error 23 min 3 min

   3. Write the email, the chat line and the note that says I do not know yet

      For one delayed project, draft the client email, the internal chat message and the meeting note. Then escalate the one thing you cannot answer

      • client_thread.eml.txt
      • contract_extract.pdf.md
      • site_status_sheet.xlsx
      planted error 21 min

   4. Turn what worked into a prompt library your team can pick up

      Package your six best prompts into a dated, reviewable library. Your team should use it on Monday without asking you how it works

      • compliance_register_extract.pdf.md
      • my_prompt_history.docx.md
      • team_task_list.csv
      planted error 22 min 3 min
5. Week 5

   Week 5 · People & Operations

   This profession

   1. Screen 200 resumes to a rubric, then audit your own shortlist watch this one

      Score 200 applications against a written rubric. Cut a shortlist of 30. Then check whether your shortlist looks like the applicant pool before it leaves your desk

      • ai_shortlist_and_rationale.docx.md
      • anonymised_candidates_200.csv
      • jd_hr_ops_executive.pdf.md
      • screening_rubric.pdf.md
      planted error 24 min 3 min

   2. Redact a candidate file before the model ever sees it

      Turn a 140-row candidate sheet carrying PAN, UAN, date of birth and current CTC into something you can safely paste into an AI tool. Keep the key that maps it back

      • ai_vendor_terms_free_tier.pdf.md
      • candidate_consent_notice_signed.pdf.md
      • candidate_master_140.xlsx
      • junior_sop_ai_screening.docx.md
      planted error 23 min

   3. Write a JD the requisition can pay for, then source 40 replies

      Draft a job description that matches the approved requisition. Then work Naukri Resdex and LinkedIn until 40 candidates have actually replied, not until 400 have been messaged

      • ai_jd_and_sourcing_plan.docx.md
      • linkedin_outreach_log.csv
      • naukri_recruiter_usage_export.csv
      • requisition_payroll_support_analyst.pdf.md
      planted error 25 min 3 min
6. Week 6

   Week 6 · People & Operations

   This profession

   1. Schedule 25 interviews across four panels and recover the no-shows

      Build a week of interview slots for 25 candidates across four panels. Then run the no-show recovery loop when six of them do not turn up on day one

      • ai_interview_schedule.xlsx
      • candidate_availability_25.csv
      • hr_calendar_next_week.pdf.md
      • panel_roster.csv
      planted error 24 min

   2. Reconcile biometric punches to payroll and clear the exception queue

      Match a month of biometric punches against the leave register before the payroll cut-off. Clear the exception queue. Hand payroll a loss-of-pay figure that survives being checked

      • ai_exception_summary.docx.md
      • biometric_punch_export_nov.csv
      • exception_queue.xlsx
      • leave_register_greythr.csv
      • payroll_master.xlsx
      planted error 26 min 3 min
7. Week 7

   Week 7 · People & Operations

   This profession

   1. Draft a candidate consent notice and answer an erasure request

      Rewrite the one-line consent tick box into a plain-language notice with one specific purpose. Then answer a rejected candidate who has asked you to delete everything you hold on her

      • ai_drafted_notice_and_reply.docx.md
      • current_consent_checkbox.png.txt
      • dpdp_rules_extract.pdf.md
      • erasure_request_email.pdf.md
      • retention_schedule.xlsx
      planted error 23 min

   2. Clear 30 helpdesk tickets against the handbook and escalate the rest

      Answer a Monday morning queue of 30 employee helpdesk tickets from the policy handbook. Pull out the ones AI answered confidently that you are not allowed to answer at all

      • ai_drafted_replies.docx.md
      • policy_handbook_v7.pdf.md
      • sla_and_escalation_matrix.pdf.md
      • ticket_queue_30.csv
      planted error 25 min 3 min
8. Week 8

   Week 8 · Dossier and evaluation

   Dossier and evaluation

   1. Hiring operations pack

      A four-page PDF plus one working file.

   2. Re-score an AI shortlist and run the adverse-impact spot check before it reaches the manager

      A 25-minute proctored practical on an unseen folder with 5 seeded defects, then a 10-minute viva.

      25 min 10 min

What you’ll build

The dossier an employer reads.

How you’re assessed

Four axes, one unseen folder.

The certificate

What it says, and how it is checked.

Certificate of Achievement Certificate of Completion

How each one is earned

• Completion: every module of the course, done.
• Achievement: pass the final evaluation at 60 % or above.
• Distinction: 80 % or above on the same evaluation.

Certified with DistinctionCertifiedNot yet certified

Verify it like an employer would

An employer pastes the serial into the verify page and has an answer in seconds. This is what the specimen serial returns, and what a real one shows.

Serial checked PG-SPEC-IMEN-PPL0-0000

Not a credential

A specimen serial is refused on every verification route - by design, it fails the checksum before any record is read.

A real certificate shows

• Whether it is valid, or has been revoked
• Who it was issued to, for which course and level
• The date it was issued, and the score
• Links to the PDF, the badge image and the machine-readable credential

Open the verify page

Add to profile

One click puts a real certificate on LinkedIn with the serial and the verify link attached. Preview only - the button appears on your certificate page.

Name

AICP · People & Operations

Issuer

PrepGraph

Credential ID

PG-SPEC-IMEN-PPL0-0000

Credential URL

courses.prepgraph.com/verify/…

Add to LinkedIn profile

Preview. Nothing is sent from this page.

The four axes

Every evaluation is scored on the same four questions.

1. 1
   Output quality

   Is the deliverable correct, complete and in a form the employer could use unedited?

2. 2
   Errors caught

   How many of the seeded defects did the candidate find, and did they document each one?

3. 3
   Data safety

   Was personal or client data redacted before any AI tool saw it, and can the candidate show the substitution?

4. 4
   Judgment under uncertainty

   When the candidate could not verify something, did they escalate, ask, or invent?

Who teaches you

A tutor that reads the same files you do.

Questions

About this course

Related courses

Other desks on the same core.

• Every file is synthetic.

  All learner-facing material is synthetic. No real client ledgers, GSTINs, PANs, resumes, patient charts, MRNs or ABHA addresses appear anywhere.

• What the certificate is.

  Evidence of supervised AI competence in a named profession. This certificate makes no placement promise and must never be marketed as one.

• You pay once.

  There is no subscription, no auto-renewal and no card details stored. Your access runs for the term stated on the course page.

• The practical is proctored.

  The proctored practical and the viva are recorded (screen and camera). The recording is retained for 180 days, is replayed only on a human-review trigger, and is released to no employer.