Generative AI in the daily work of a Business Analyst Training Course
This instructor-led, live training (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level individuals who wish to learn how to leverage Large Language Models to break through creative blocks, structure chaotic workshop data, and automate repetitive documentation tasks. In the age of digital transformation, Generative AI (GenAI) is becoming a crucial "copilot" in analytical tasks. This course focuses not just on the technology itself, but on its practical implementation within the Business Analysis Life Cycle. The training methodology emphasizes the "human-in-the-loop" approach, teaching how to maintain a critical eye and ensure the highest quality of AI-supported analytical deliverables.
By the end of this training, participants will be able to:
- Understand the real capabilities and limitations of GenAI models (e.g., hallucinations, context windows).
- Be able to use AI as an advanced tool supporting thought and analytical processes.
- Learn how to create precise requirement structures and technical documents using AI.
- Accelerate conceptual work, from hypothesis generation to documentation drafting.
- Consciously evaluate the quality and substantive correctness of AI-generated outputs.
- Gain knowledge on the safe and ethical use of AI tools concerning corporate data.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This course is available as onsite live training in Croatia or online live training.
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 a role related to data analysis, reporting, or business process support.
- Technical skills: Proficiency in MS Excel (lookup functions, pivot tables, basic charting).
- Domain knowledge: Basic understanding of Key Performance Indicators (KPIs) within one's business area and familiarity with the data lifecycle in an organization.
Audience
- Business and Systems Analysts.
- Product Owners and Product Managers.
- Business Consultants.
- Requirements Engineering Specialists.
Open Training Courses require 5+ participants.
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Testimonials (2)
Friendly, plenty of breaks to think about what we have learnt and lovely guy.
Leanne - Welsh Revenue Authority
Course - Agile Business Analysis
comparing theory to practical life
Olaf - Bank Millennium S.A.
Course - Business Analysis, BABOK V3.0 and IIBA Certification Preparation
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