Generative AI in the daily work of a Business Analyst Training Course
This instructor-led, live training (available online or on-site) is designed for beginners, intermediate learners, and advanced professionals who want to master how Large Language Models can help overcome creative barriers, organize chaotic workshop data, and automate routine documentation tasks. In today's digital transformation landscape, Generative AI (GenAI) has become an essential "copilot" for analytical work. This course goes beyond just explaining the technology, focusing instead on its practical application within the Business Analysis Life Cycle. The training methodology emphasizes a "human-in-the-loop" approach, teaching participants how to maintain critical oversight and ensure the highest quality of AI-supported deliverables.
Upon completing this training, participants will be able to:
- Grasp the actual capabilities and limitations of GenAI models (such as hallucinations and context window constraints).
- Utilize AI as an advanced tool to support cognitive and analytical processes.
- Learn how to generate precise requirement structures and technical documents using AI.
- Speed up conceptual work, from formulating hypotheses to drafting documentation.
- Consciously assess the quality and substantive accuracy of AI-generated outputs.
- Acquire knowledge regarding the secure and ethical use of AI tools in relation to corporate data.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live-lab environment.
Customization Options for the Course
- To request customized training for this course, please get in touch to arrange it.
Course Outline
Fundamentals and Applications of Gen AI
- Introduction to Generative AI
- What is Gen AI and how it works
- Language models and their limitations
- The role of humans in AI-assisted work
2. Gen AI for the Business Analyst
- Support in problem analysis
- Information structuring
- Drafting documents and reports
3. Prompting in practice
- How to formulate effective prompts
- Context, objectives, and constraints
- Iterative refinement of outputs
4. Supporting business analysis
- Defining business problems
- Formulating hypotheses
- Scenario analysis
5. AI-assisted analytical documentation
- Business requirements
- Process descriptions
- Workshop notes and summaries
Integrating AI into daily workflow
- Gen AI as a thinking aid, not a replacement
- Critical assessment of AI outputs
- Content verification and validation
- Avoiding thoughtless automation
2. AI in stakeholder communication
- Preparing communications and updates
- Simplifying complex content
- Tailoring messages for different audiences
3. Risks and responsibility
- Data privacy and confidentiality
- Accountability for AI-generated content
- Ethical considerations
4. Building a custom BA workflow with AI
- Practical use-case scenarios
- Integration with productivity tools
- Team best practices
Requirements
- Professional experience in roles related to data analysis, reporting, or business process support.
- Technical skills: Proficiency in MS Excel (including lookup functions, pivot tables, and basic charting).
- Domain knowledge: A fundamental understanding of Key Performance Indicators (KPIs) within one's business area and familiarity with the organizational data lifecycle.
Target Audience
- Business Analysts and Systems Analysts.
- Product Owners and Product Managers.
- Business Consultants.
- Requirements Engineering Specialists.
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
Generative AI in the daily work of a Business Analyst Training Course - Enquiry
Testimonials (2)
the practical part
Daniela Mirevska
Course - Business Process Modelling in BPMN 2.0
The trainer shared his knowledge and led great atmosphere.
Agnieszka Dubanska - Narodowy Fundusz Zdrowia
Course - Modelowanie procesów biznesowych z wykorzystaniem UML i BPMN
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