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PROGRAM 33 · TEAM TRAINING

AI & Data for Product Managers

From customer insight to launch, faster and with better decisions.

8 sessions3 modules4 hands-on projects3 days · 9 am–5 pmCertificate on completion
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Request a proposalSee the curriculum

Who this course is for

  • Product managers and product owners
  • Business analysts and associate PMs
  • UX researchers and product designers
  • Product teams in fintech, e-commerce, SaaS, telecom and edtech

What your team will be able to do

  • Turn interviews, reviews and support tickets into clear problem statements
  • Write PRDs, user stories and acceptance criteria in hours
  • Read product data, plan experiments and prioritise with evidence
  • Deploy four working automations for your product team
How it runs

3 days at your office, 8 sessions

Three sessions a day plus a hands-on build lab every afternoon. Day 3 ends with capstone presentations.

Day 1

9:00 am – 5:00 pm

AI chatbots for product management work

9:00–10:30S1Prompt engineering for product management
10:30Tea break
10:45–12:15S2Customer insight & discovery
12:15Lunch & prayer
1:00–2:30S3PRDs, stories, roadmaps & launch
2:45–4:30LABBuild lab: research synthesis on your own files
4:30–5:00Q&A and day recap

Day 2

9:00 am – 5:00 pm

Analysis, then the first two builds

9:00–10:30S4Formulas & product data cleaning
10:30Tea break
10:45–12:15S5Product analytics & product decisions
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant and alerts
2:45–4:30LABBuild lab: metrics dashboard, assistant and alerts
4:30–5:00Q&A and day recap

Day 3

9:00 am – 5:00 pm

Last two builds and the capstone

9:00–10:30S7Project 03: Feature request triage
10:30Tea break
10:45–12:15S8Project 04: User feedback extraction
12:15Lunch & prayer
1:00–3:00LABCapstone build clinic
3:15–4:30LABCapstone presentations
4:30–5:00Certificates and next steps
Group: 10–40 people from one organisationSame content and projects in both formatsBangla delivery with English technical termsEvery session ends with a deliverable
Curriculum

8 sessions, one build in each

3 modules · 8 sessions · 4 hands-on projects

PART 1AI Chatbots for Product Management WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for product management work (research synthesis, PRDs and user stories, release notes, product data analysis)
  • Free vs paid tiers; a workflow that needs no international payment card
  • Bangla vs English output quality; when to draft in English and translate
  • Which tool for a long document, which for a formula, which for a polished letter

Prompt Engineering Fundamentals

  • What a prompt is; why the same question gives different answers
  • The four-part structure: role, context, task, output format
  • Role prompting: act as a product manager, business analyst, UX researcher or growth analyst
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own product management work
  • Step-by-step reasoning for multi-part tasks such as prioritising ten feature requests with different reach, effort and revenue impact
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a PRD (problem → users → goals → requirements → stories → metrics → launch plan) into a sequence of smaller steps

Iteration & Prompt Library Building

  • Why the second prompt matters more than the first; refining instead of restarting
  • Diagnosing a bad output: vague instruction, missing context or wrong tool
  • Building reusable prompt templates for repeated product management tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: user personal data, unreleased roadmaps, source code and API keys, pricing strategy, investor or partner terms
  • Anonymising data before prompting; safe vs unsafe product management use cases
  • Hallucination awareness; verifying every figure, date, name and legal reference
  • The verification rule: AI drafts, a person checks before anything leaves the building
DELIVERABLEa personal prompt library of 10 templates for your repeated product management tasks.
PART 2Product Management Data Analysis in Excel & Google SheetsSessions 4–5
PART 3Applied Projects: AI Assistants & AutomationSessions 6–8
Applied projects

Four automations, running in your organisation

01Session 6

Product Knowledge Assistant

Support, sales and operations colleagues get answers from your PRDs, release notes and help centre articles, with the section cited.

  1. INPRDs, release notes & help centre
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

Release & Compliance Alert Engine

Release dates, app store deadlines, certificate and licence renewals and experiment end dates checked daily, with alerts 30, 15 and 7 days ahead.

  1. INRelease & renewal tracker
  2. RUNDaily Make scenario
  3. OUTAlert to the responsible owner
Built with Make · Sheets · Gmail
03Session 7

Feature Request Intake & Triage

Requests from sales, support and operations logged, de-duplicated and routed to the owning PM, with the requester told the decision.

  1. INFeature request form
  2. RULESTriage routing script
  3. OUTDecision sent to the requester
Built with Apps Script · Forms
04Session 8

User Feedback Extraction Pipeline

Reviews, support emails and survey exports tagged by theme, sentiment and severity, with urgent issues flagged and weekly theme counts.

  1. INReviews, emails & surveys
  2. AIGemini structured extraction
  3. OUTTagged rows & theme counts
Built with Gemini API · Drive

Capstone presentation

Each person presents one automation built for their own workplace.

Day 3 afternoon
Applied across every session

Responsible & Ethical AI in Product Management

Fairness & Non-Discrimination

  • Where bias enters product management decisions: data, wording, criteria and past patterns
  • Proxy discrimination: address, age, gender or background inferred indirectly

Privacy & Data Protection

  • Data minimisation: collect only what the decision requires
  • Retention and deletion of user, customer and research participant data

Responsible Product Design

  • No dark patterns: hidden fees, forced consent or tricky cancellation
  • Designing for users with low literacy and low-end phones

Accountability & Human Oversight

  • Human-in-the-loop by design: AI recommends, a named person decides
  • Who owns an AI-assisted decision when it is challenged

Workforce Impact & Your AI Use Policy

  • Talking to product management teams about AI without triggering job-loss fear
  • Reskilling and role redesign as AI absorbs routine work
Outcomes

By the end, your team can

  • Choose the right AI tool and write prompts that work first time
  • Maintain a prompt library covering your repeated product management tasks
  • Turn interviews, reviews and tickets into clear problems worth solving
  • Write PRDs, stories, roadmaps and launch kits quickly
  • Read product metrics, cohorts and experiments with confidence
  • Build and deploy automations with Make, Apps Script and the Gemini API
  • Apply fairness, transparency and privacy to every AI-assisted decision

And leaves with

A research synthesis and persona set
A PRD, user story and roadmap template set
A product metrics dashboard with funnel and cohorts
A grounded product knowledge assistant your colleagues can use
A release & compliance alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own product team

Tools your team will use

Chatbots
ChatGPTGeminiClaudeCopilotDeepSeek
Content
CanvaGammaCapCutGoogle Slides
Data
Microsoft ExcelGoogle SheetsPower Query
Workspace
GmailCalendarMeetFormsDrive
Automation & AI builds
MakeGoogle AI StudioApps ScriptGemini API
Product Management tools
Google AnalyticsFirebaseMixpanel exportsFigmaJira

What participants need

  • A laptop with Excel and a Google account
  • Basic Excel comfort and an export of product usage data or user feedback
  • One real work file to practise on from Session 2
  • No coding background required; free tiers only

How your team will learn

  • build-along classes (you work while the trainer works)
  • practise on your own workplace file, not dummy data
  • every session ends with a deliverable
  • Bangla delivery with English technical terms
  • recordings, prompt library and setup guides
  • certificate after capstone submission
Request a proposal

Bring this program to your product team

Tell us about your team. We reply within one working day with a plan built around your own documents and workflows.

  1. 1 · A short discovery call with your product lead
  2. 2 · We tailor examples to your masked files
  3. 3 · Offline at your office, or online live classes
Chat on WhatsApp
Request a proposal