Generative AI in the daily work of a Business Analyst Training Course
This instructor-led, live training (available online or onsite) is designed for beginner-level, intermediate-level, and advanced-level professionals who wish to learn how to leverage Large Language Models to overcome creative blocks, organize unstructured workshop data, and automate repetitive documentation tasks. In the era of digital transformation, Generative AI (GenAI) has become an essential "copilot" for analytical work. This course emphasizes not only the technology itself but also its practical application throughout the Business Analysis Life Cycle. The training methodology highlights a "human-in-the-loop" approach, teaching participants how to maintain critical oversight and ensure the highest quality of AI-supported analytical deliverables.
By the end of this training, participants will be able to:
- Grasp the actual capabilities and limitations of GenAI models (e.g., hallucinations, context windows).
- Utilize AI as an advanced tool to support thought processes and analytical workflows.
- Learn how to craft precise requirement structures and technical documents using AI.
- Accelerate conceptual work, from generating hypotheses to drafting documentation.
- Consciously evaluate the quality and substantive accuracy of AI-generated outputs.
- Acquire knowledge on the safe and ethical use of AI tools regarding corporate data.
Format of the Course
- Interactive lectures and discussions.
- Extensive exercises and hands-on practice.
- Practical implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
This course is available as onsite live training in Taiwan 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 roles 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 organizational data lifecycles.
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)
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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