Școala informală de IT

AI for Business Professionals – Curriculum

Școala Informală de IT

Curriculum AI for Business Professionals

Objective: This course is designed for anyone who wants to learn how Business Analysts can utilize AI in their product development practices and how to build AI-powered features. Equip professionals with the knowledge and skills to apply artificial intelligence tools and techniques for solving complex business problems, improving decision-making processes, and gaining insights from data.Target Audience: Business analysts, data analysts, and professionals interested in integrating AI into business analysis processes and their products.
Duration: 20 hours divided into 8 modules of 2.5 hours each, spanning one month

Delivery Method: The course will be a blend of lectures, hands-on workshops, case studies, and project work.
Prerequisites: Basic understanding of business analysis principles and practices. Familiarity with basic statistics and data analysis is advantageous but not required.

Course structure

1 Introduction to AI in business 

  • Meet and Greet. Course agenda. 
  • Understanding AI and its relevance in today’s business world 
  • What is AI and what are the different types of AI. 

2 Using AI as a business professional 

  • Main ways to leverage AI in your day to day activities 
  • An overview of different types of AI Tools 
  • Prompt engineering useful tips 

3 AI in Requirements Elicitation 

  • Integrating AI in business analysis activities 
  • Getting help from AI during project initiation 
  • Requirements elicitation with the help of AI 
  • Accelerate requirements validation with AI

4 AI in Solution Design 

  • AI for more creative Ideation and conceptualization 
  • Slashing your documentation efforts 
  • Enhanced User experience design 
  • Sentiment analysis and customer feedback analysis 

5 AI helps cater for your customers 

  • Rethinking your knowledge base with AI 
  • AI Chatbots and virtual assistants in customer service Hyper customized customer experiences 

6 Data Management and Quality for AI 

  • Importance of data quality and management in AI 
  • Data collection, cleaning, and preparation 
  • Understanding data warehouses and lakes 
  • Basic statistics and data analysis techniques using AI 

7 Integrating AI in your software products 

  • AI project lifecycle: From conception to deployment 
  • Identifying business opportunities for AI solutions 
  • Developing an AI strategy and roadmap 
  • AI Powered automations 

8 Conclusions about using AI as a business professional 

  • Ethical considerations in AI applications 

Emerging trends in AI and their potential impact on business analysis Retrospective and lessons learned

Additional Components: 

Hands-on Workshops: Practical sessions on using AI tools and performing data analysis tasks. 

Project (optional): Participants will propose an AI solution for a real business problem, covering project planning to proposed implementation.