Unleashing AI for Business Analysis: Mastering Practical Applications for Success Course
April 15 - 17, 2024 (3 Days)
9:00 am (Central) until 5:00pm (Central)
Online - Live Instructor
April 15 - 17, 2024 (3 Days)
9:00 am (Central) until 5:00pm (Central)
Online - Live Instructor
April 15 - 17, 2024 (3 Days)
9:00 am (Central) until 5:00pm (Central)
Online - Live Instructor
Course Description:
This course is designed to teach participants how to effectively use AI and ChatGPT 4 in the context of business analysis, focusing on eliciting, modeling, and analyzing requirements. It integrates key concepts from Natural Language Processing, Data Mining, Machine Learning, and Sentiment Analysis to enhance the requirements engineering process. Participants will also learn about automated documentation techniques to streamline their workflows.
Learning Outcomes:
Participants will learn to:
Efficiently use AI and ChatGPT 4 for eliciting business requirements from stakeholders and the ability to use other AI NLPs
Apply NLP and ML techniques to model and analyze requirements
Leverage Sentiment Analysis for understanding stakeholder feedback
Automate the documentation process for requirements engineering
Target Audience:
Business Analysts
Requirements Engineers
Project Managers
IT Consultants
Product Managers
Prerequisites:
Understanding of business analysis and requirements engineering
Understanding common business analysis techniques (use case modeling, stakeholder analysis, functional decomposition, and others)
Understanding Agile principals and artifacts (epics, user stories, acceptance criteria)
Familiarity with software development processes (SDLC)
Access to ChatGPT version 4. ChatGPT version 3.5 will have less functionality
You will need to download examples and data files to your local system.
You will need to upload case study data to ChatGPT via a prompt
Number of prompts limits may apply
Course Duration:
3 Days
Course Contents:
Module 1: Introduction to ChatGPT 4 and Requirements Engineering
Overview of ChatGPT 4 capabilities
Understanding the components of AI
The Role of AI and ChatGPT in requirements elicitation, modeling, and analyzing
Setting up your environment - tools, security and privacy
Module 2: Fundamentals of Natural Language Processing (NLP)
Introduction to NLP and its relevance to requirements engineering
Key NLP techniques and their applications as part of ChatGPT and AI
AI integration into Business Analysis - requirements elicitation, requirements modeling, solution design, market analysis, customer analysis, and more
Module 3: Eliciting Requirements with ChatGPT 4
Strategies for using AI and ChatGPT 4 to gather requirements from stakeholders
Designing prompts, MEGA prompts, and prompt chaining
ChatGPT acting like an expert
Using AI and ChaptGPT for creating diagram prompts, diagrams, and visuals
Module 4: Modeling Requirements with ChatGPT 4
Define and create epics for Agile
Define and create user stories
Creating acceptance criteria for user stories - Given, When, Then
Creating a Use Case Model
Creating a context diagram - stakeholders, capabilities, data flows
Creating a functional decomposition diagram - capabilities, features, functions, functional, non-functional
Creating a stakeholder analysis utilizing the Salience model
Create concept mapping for products
Identifying and Creating Personas - customer and market segments
Create a customer journey map
Modifying a customer journey map
Creating process flows
Modifying process flows
Decision making - creating decision trees, pros and cons, acting as a sparring partner, implications of making a decision, elaborating consequences for a decision
Writing waterfall requirements - establishing scope, stakeholders, planning, elicitation sessions, document analysis, documenting requirements, prioritizing requirements, validate requirements, refine and finalize requirements
Module 5: Advanced NLP for Requirements Analysis
Sentiment Analysis to gauge stakeholder preferences and concerns
Entity Recognition and Relationship Extraction in requirements documents
Module 6: Introduction to Machine Learning and Data Mining in Requirements Engineering
Basics of ML and Data Mining and their application in analyzing requirements
Pattern recognition in requirements to identify inconsistencies and dependencies
Understanding dependencies, summarizing findings, planning validation and clarification with stakeholders
Module 7: Analyzing Requirements with ChatGPT 4
Advanced techniques for analyzing and prioritizing requirements
Identifying business value
Assess implementation complexity
Determine risk levels
Stakeholder interest analysis
Cost benefit analysis
MoSCoW prioritization method
Kano Model Analysis
Generating insights and actionable items from data
Module 8: Documentation of Requirements
Techniques for automated generation of requirements documents
Using ChatGPT 4 to create, update, and maintain requirement specifications
Best practices for automated documentation
Module 9: Sentiment Analysis in Stakeholder Feedback
Leveraging sentiment analysis to understand stakeholder feedback
Customer and focus group sentiment analysis
Market analysis and customer trends