Skip to content
PROGRAM 39 · TEAM TRAINING

AI & Data for Research & Academia

Read more, write better, and analyse data with confidence.

Important: AI supports research but never replaces it. Every citation must be checked, and AI use must follow the university's or journal's academic integrity and disclosure rules.

Who books it: Universities, research institutes, graduate programmes, faculty development units and research NGOs.

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

Who this course is for

  • University faculty, lecturers and research supervisors
  • Master's and PhD researchers
  • Research officers in institutes, think tanks and development organisations
  • Public health, social science, business and engineering researchers

What your team will be able to do

  • Find, summarise and compare literature with every source verified
  • Clean and analyse survey data with AI help in Excel, R or Python
  • Improve academic writing while keeping it your own work
  • Deploy four working automations for your department or research 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 research work

9:00–10:30S1Prompt engineering for research
10:30Tea break
10:45–12:15S2Literature review & research design
12:15Lunch & prayer
1:00–2:30S3Academic writing & teaching support
2:45–4:30LABBuild lab: verified literature table on your own work
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 & research data cleaning
10:30Tea break
10:45–12:15S5Research analytics & defensible findings
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant and alerts
2:45–4:30LABBuild lab: analysis report, 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: Research request approvals
10:30Tea break
10:45–12:15S8Project 04: Paper & data 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 Research WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for research work (literature summaries, long PDF reading, R and Python code, academic English editing)
  • 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 research supervisor, statistician, journal reviewer or academic editor
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own research work
  • Step-by-step reasoning for multi-part tasks such as choosing a sampling method or the right statistical test for a hypothesis
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a literature review (search → screen → summarise → compare → synthesise → write) 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 research tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: identifiable participant data, unpublished manuscripts under review, students' grades and personal details, ethics committee files, grant budgets
  • Anonymising data before prompting; safe vs unsafe research 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 research tasks.
PART 2Research 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

Research & Regulations Assistant

Students and new faculty get answers from your academic regulations, thesis guidelines and research ethics policy, with the section cited.

  1. INRegulations, ethics & thesis rules
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

Research Deadline & Compliance Alerts

Grant, ethics approval, journal, thesis and subscription deadlines checked daily, with alerts 30, 15 and 7 days ahead.

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

Research Request & Approval Workflow

Proposals, fieldwork and ethics requests routed to the supervisor, then the department head or ethics committee, logged with a reference number.

  1. INResearch request form
  2. RULESApproval routing in Make
  3. OUTLogged approval with reference
Built with Make · Forms · Sheets
04Session 8

Paper & Data Extraction Pipeline

A folder of paper PDFs becomes a literature matrix, with unverifiable DOIs flagged and every row marked unchecked until reviewed.

  1. INResearch paper PDFs
  2. AIGemini structured extraction
  3. OUTLiterature matrix in your sheet
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 Research

Fairness & Non-Discrimination

  • Where bias enters research 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 participant, student and respondent data

Research Integrity & Participant Protection

  • No fabricated data, citations or results under any deadline pressure
  • Informed consent and anonymity for every participant

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 research 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 research tasks
  • Build a verified literature review with AI support
  • Clean and analyse survey and interview data with defensible methods
  • Improve writing and teaching material while keeping academic integrity
  • 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 literature review workflow and a verified review table
A cleaned dataset with codebook and analysis report
A teaching kit with course outline, rubric and AI use rule
A grounded research & academic regulations assistant your colleagues can use
A research deadline & compliance alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own department or research 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
Research tools
ZoteroGoogle ScholarElicit or ConsensusKoboToolboxR or Python (Colab)

What participants need

  • A laptop with Excel and a Google account
  • An active research project, thesis or course to work on; basic statistics helps
  • 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 research 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 research 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