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Duration 14 hours
Course Outline
Core Principles and Practical Uses of Gen AI
Introduction to Generative AI
- Defining Gen AI and exploring its operational mechanisms
- Language models and their inherent constraints
- The crucial role of human oversight in AI-assisted tasks
Gen AI for Business Analysts
- Aiding in the analysis of complex problems
- Structuring and organizing information
- Drafting professional documents and reports
Practical Prompting Techniques
- Crafting effective and precise prompts
- Managing context, objectives, and limitations
- Refining outputs through iterative processes
Enhancing Business Analysis
- Identifying and defining core business challenges
- Formulating and testing hypotheses
- Conducting scenario-based analyses
AI-Supported Analytical Documentation
- Articulating business requirements
- Describing business processes
- Documenting workshop notes and generating summaries
Embedding AI into Everyday Workflows
Gen AI as a Cognitive Aid, Not a Substitute
- Critical evaluation of AI-generated responses
- Verifying and validating content accuracy
- Preventing uncritical or thoughtless automation
AI in Stakeholder Interaction
- Preparing status updates and communications
- Simplifying complex topics for clarity
- Tailoring messages to suit different audience groups
Risks and Professional Responsibility
- Maintaining data privacy and confidentiality
- Accepting accountability for AI-generated material
- Addressing ethical implications
Developing a Customized BA Workflow with AI
- Exploring practical application scenarios
- Integrating AI with existing productivity suites
- Establishing team-oriented best practices
Requirements
- Practical experience in roles associated with data interpretation, reporting, or business process assistance.
- Technical proficiency: Competence in MS Excel, particularly with lookup functions, pivot tables, and fundamental charting.
- Industry context: A foundational understanding of Key Performance Indicators (KPIs) relevant to your sector and familiarity with how data lifecycle processes operate within an organization.
Target Audience
- Business and Systems Analysts.
- Product Owners and Product Managers.
- Business Consultants.
- Requirements Engineering Specialists.
Testimonials (2)
the practical part
Daniela Mirevska
Course - Business Process Modelling in BPMN 2.0
The trainer shared his knowledge and led great atmosphere.