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AI for Business Analysts: Prompts That Repeat, 530+ Tools
449 students
AI for Business Analysts: Prompts That Repeat, 530+ Tools
AI wrote something that read well and meant little? AI for business analysts: requirements, prompts, agents, data
Last updated 9/2026
English
What you'll learn
- Turn AI from a chat into a repeatable working system: take 530+ ready AI prompts, templates, procedures and checklists in 112 downloadable resources
- Frame a business problem before writing a requirement, with a business analyst interview script, a stakeholder register and a requirements elicitation tracker
- Write user stories with acceptance criteria and keep requirements traceable with a requirements traceability matrix
- Model AS-IS and TO-BE processes, describe them in BPMN and analyse the impact of a change request
- Build prompts with a prompt architecture toolkit, a prompting technique selector and chain-of-thought, tree-of-thoughts and ReAct
- Move from prompting to context engineering with projects, retrieval over your own documents and memory
- Build an AI operating layer: projects with their own knowledge base, Skills that run a workflow the same way every time, and connectors
- Package your Skills into a plugin with the HR Plugin skeleton and a 90-day rollout workbook
- Analyse data end to end: data quality audit, exploration, diagnosis of causes, an interpretable risk forecast and a board-ready presentation
- Learn with Mike, the #1 HR instructor on Udemy: 1,800,000+ enrollments, 170,000 students, about 200 books on Amazon
Explore related topics
Course content
14 sections • 37 lectures • 19h 5m total length
Requirements
- Experience in business analysis, operations, HR or any role that writes documents and analyses data
- Access to an AI assistant such as ChatGPT or Claude; a paid plan helps for the projects and Skills sections
- Nothing to buy for the course itself: the presentations and 75 working files are attached to the lectures
- English at intermediate level or above, since all lessons are in English
Description
This course contains the use of artificial intelligence.
Most analysts have tried AI, received something that read well and meant little, and quietly gone back to writing everything themselves. The output was weak because the input was a sentence. Here are 533 tools to give it structure: 381 ready-to-use AI prompts, templates, procedures, checklists and matrices, 57 models and methods, 20 services shown on screen and 75 working files.
Open a lecture, take the template, build one document you write every week.
Why the first attempt disappoints
You asked for a document and got a plausible one with invented specifics. You asked for analysis and got a summary of what you had already written. The model had no access to your policies, definitions or templates, so it answered from the general internet. And every time you wanted the same output again, you rebuilt the request from scratch, so nothing accumulated.
What changes after this course
Requirements start from a framed problem and stay traceable. Processes are described before they are automated. Your prompts have a structure, your context is loaded once and reused, and a Skill runs the same workflow every time. Data goes from a raw export to a defended presentation. And the whole set can be installed by your team as one package.
A note on the examples
The AI sections are taught on people and operations data: recruiting, onboarding, reviews and pay. The methods are domain-neutral: a Skill, a retrieval setup or an analysis cycle works on any dataset. The examples are kept as recorded, because a real dataset teaches more than an invented one.
What is inside: 533 tools, counted lecture by lecture
You do not have to take this number on trust. Open any lecture and read its description: every tool inside is listed there by name.
- 112 downloadable resources: the lecture presentations plus 75 working files, from business analysis templates and prompt libraries to project templates, Skills bundles and analysis workbooks
- 381 ready-to-use tools inside the presentations:
- 183 ready AI prompts: requirements extraction from meeting transcripts, user story generation, requirements prioritization, TO-BE process improvement analysis
- 53 templates and sample documents: business problem statement, user stories, Given–When–Then acceptance criteria, business requirements document
- 49 step-by-step procedures and workflows: requirements elicitation interviews, requirements conflict resolution, AS-IS/TO-BE process analysis, change request impact analysis
- 31 checklists: INVEST user story quality, acceptance criteria quality, non-functional requirements, process audits
- 25 scorecards, rubrics and matrices: stakeholder power-interest grid, elicitation technique selection, value-effort prioritization matrix, requirements traceability matrix
- 14 question lists and scripts: root problem diagnosis, value discovery interviews, business analyst stakeholder interviews, bottleneck identification
- 14 formulas and metric sets: requirements elicitation performance, requirements documentation quality, process efficiency, prompt quality
- 12 other working tools: MoSCoW prioritization, value-added activity classification, context placement decision rules
- 57 models and methods explained with examples: BABOK business analysis, Business Model Canvas, BPMN process modeling, few-shot prompting
- 20 services shown on screen, including Claude, ChatGPT, Perplexity, Notion and n8n
Where the tools are
- Start here (1 tool). The Four-week first draft plan workbook.
- The analyst's craft (4 sections, 155 tools). Problem framing, requirements, user stories, processes, systems thinking, BPMN and process projects.
- AI fundamentals (2 sections, 125 tools). What AI can and cannot do, working with files, custom assistants and advanced techniques.
- Prompt architecture and context (2 sections, 61 tools). Prompt structure, chain-of-thought, tree-of-thoughts, ReAct, projects, retrieval, MCP and agents.
- The AI operations layer (3 sections, 114 tools). Projects, Skills, connectors, document generation, structured output and plugins.
- Data analysis with AI (2 sections, 91 tools). Preparation, exploration, diagnosis, forecasting and presenting to a sceptical audience.
Who is teaching
I am Mike, the #1 HR instructor on Udemy, with 1,800,000+ course enrollments from 170,000 students, and the author of about 200 books on Amazon. I built the people system at Preply as it became a unicorn and worked at Wargaming, iDeals and Alfa-Bank across 20 years in HR. I hold PHRi, SHRM-CP and HCI sHRBP certifications and represent HRCI in Eastern Europe. I am also a founder and lead the strategy of my own academy.
When I did HR analytics, there was no AI, and a lot was done by hand in Excel. Out of curiosity I later ran my old tasks through Claude, and work that used to take me a week took a couple of hours: a few prompts, a few comments, a few corrections. I also use Claude to write messages for our Telegram channel, and the key is saying exactly which format I need: when I ask for Telegram markup, I get a finished message ready to paste.
How to use the course
Start with the analyst's craft if requirements are your daily work, or with the AI sections if you already write them. Build one Skill for the document you write most often as you go. Section and lecture titles show how many tools are inside, and each lecture description lists them by name.
What is included
- 37 lectures across 14 sections, 19 hours
- 112 downloadable resources: lecture presentations and 75 working files
- 533 tools across the lessons, including 20 services shown on screen
- Lifetime access to all materials
- Active instructor support in the Q&A section
- A Udemy Certificate of Completion
Where to start
Take the document you write most often and build it as a Skill during the course. Enrol now and start your first lesson today.
Who this course is for:
- Business analysts who want AI to produce usable documents, not drafts to rewrite
- Product and operations analysts who build requirements and process models
- HR and people analytics specialists who analyse workforce data
- Team leads who want one AI workflow the whole team can run
- Consultants who build AI assistants and Skills for clients