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Duration 14 hours
Course Outline
Gen AI: Fundamentals and Practical Applications
Foundations of Generative AI
- Defining Gen AI and understanding its operational mechanics.
- Exploring language models and their inherent limitations.
- The essential role of human oversight in AI-assisted tasks.
Gen AI for the Business Analyst
- Assisting with problem identification and analysis.
- Structuring and organizing complex information.
- Drafting professional documents and reports.
Practical Prompt Engineering
- Techniques for crafting effective and precise prompts.
- Defining context, objectives, and constraints.
- Refining outputs through iterative feedback loops.
Enhancing Business Analysis
- Clearly defining business problems.
- Formulating and testing hypotheses.
- Conducting scenario analysis.
AI-Assisted Analytical Documentation
- Documenting business requirements.
- Describing business processes.
- Summarizing workshop notes and meeting outcomes.
Integrating AI into Daily Workflows
Gen AI as a Cognitive Aid
- Critical assessment of AI-generated content.
- Verifying and validating outputs for accuracy.
- Preventing blind automation and maintaining professional judgment.
AI in Stakeholder Engagement
- Preparing clear communications and status updates.
- Simplifying complex concepts for clarity.
- Tailoring messages for diverse stakeholder groups.
Risks and Accountability
- Maintaining data privacy and confidentiality.
- Assuming responsibility for AI-generated content.
- Navigating ethical considerations in AI use.
Developing a Custom BA Workflow with AI
- Applying practical use-case scenarios.
- Integrating AI with existing productivity tools.
- Adopting team best practices for AI adoption.
Requirements
- Professional background in roles related to data analysis, reporting, or business process support.
- Technical proficiency: Competence in MS Excel, including lookup functions, pivot tables, and basic charting.
- Domain awareness: A foundational understanding of Key Performance Indicators (KPIs) within your specific business area, along with familiarity with organizational data lifecycles.
Target Audience
- Business and Systems Analysts.
- Product Owners and Product Managers.
- Business Consultants.
- Requirements Engineering Specialists.
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