Business analysis in IT with AI integration
Course Goal
To acquire practical business analysis skills in IT with the integration of artificial intelligence tools for optimizing processes, working with requirements, and supporting decision-making.
This Course is Designed For
- Beginners who want to enter IT as business analysts
- Professionals from related fields
- Specialists who want to upgrade their qualifications
- Those who want to work at the intersection of analytics and artificial intelligence
- Individuals preparing for professional certifications
Training Format:
- Recorded course
- 20 online sessions of 1.5 hours each + homework assignments
- Practical cases and homework assessment
- Support for participants in a private chat throughout the course
What Will Graduates Gain?
Program of the course "Business analysis in IT with AI integration"
1
- Software Development Life Cycle (SDLC)
- Industry and IT roles overview
- Business analyst roles
2
- Models: waterfall, prototyping, spiral model, V-model, Agile approach.
- Methodologies and frameworks: Scrum, Kanban, Lean, SAFe.
3
- Standards and certifications: BABOK, PMI-PBA, PSPO
- Ethics and quality in business analysis
- Artifacts at each stage of the SDLC
4
- Full stakeholder management cycle
- BA as a facilitator
- How to build effective cooperation
5
- Product life cycle
- Business value and its metrics
- Product vision (Vision document) as a core document
- Understanding end users
- MVP - defining the minimum viable product
6
- Levels (types) and categories of requirements (functional and non-functional)
- Requirements elicitation techniques
- Types of requirement documentation
7
- User Stories and Acceptance Criteria
- Use Cases
- DoR (Definition of Ready)
- DoD (Definition of Done)
- INVEST - investing in high-quality requirements
8
- Requirements life cycle
- Techniques for prioritizing and refining requirements (Backlog Refinement)
- Change log as a change management artifact
- Risk matrix
- Jira and Confluence in BA work
9
- Decomposition and process visualization
- BPMN 2.0
- Basics of UML
10
- Tools: Draw.io, Figma, Canva
- Creating interactive prototypes
- Usability principles
11
- How to write effective prompts
- Using AI to prepare for requirements elicitation
- Generating functional and non-functional requirements with AI
12
- Types of software development, programming languages, and tools
- Software architecture
- Database fundamentals
- APIs and data formats
13
- DevOps culture
- CI/CD and software quality
- How BA collaborates with developers, architects, and DevOps
14
- Diagram creation with AI
- Prioritization with AI assistance
- AI for rapid UI mockup creation
15
- Concept of quality
- Internal and external product quality
- Product quality metrics (KPIs)
- Interaction with QA testers
- Participation in acceptance testing
16
- Selecting a case (in agreement with NBU)
- Forming requirements and initial documentation
- Work in Confluence, Jira, Notion
17
- Creating diagrams and prototypes
- Preparing presentation materials
- Work in Confluence, Jira, Notion
18
- AI as an assistant throughout the business analysis process
- Principles of AI assistants
- Configuring an AI assistant
- Ethical aspects of AI usage
19
- Basics of effective pitching and presenting a solution
- Working with feedback and comments
- Strong communication strategies
- AI tools for creating presentations
20
- Presenting the work
- Reflection and course retrospective
- Individual development planning
Course
10 weeks
30 hours
Education provides
Marina Melnick
Founder, CEO, Lead Trainer, AI Transformation Consultant, Career Therapist