Data-Driven Business Intelligence with AI (E-MBA140)
In an era defined by rapid technological advances and ever-expanding data, business executives and managers must be able to turn raw information into actionable insights. This hands-on course equips participants with practical skills in using Artificial Intelligence (AI) to handle structured and unstructured data, harness AI as a synthetic information source, design effective A/B tests, and integrate behavioral economics principles to better understand customer needs. Participants will gain firsthand experience with AI-driven data extraction, processing, visualization, and analytics—ensuring that they can leverage data for immediate impact in their organization.
The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage," Paul Daugherty, Chief Technology and Innovation Officer at Accenture.
Why Enroll?
- Practical Focus: Learn AI-driven techniques that can be applied right away, from cleaning raw datasets to creating visually compelling reports.
- Career Enrichment: Demonstrate expertise in AI-powered business intelligence, showcasing the ability to enhance decision-making in any sector.
- Hands-On Learning: Work through realistic scenarios and case studies, culminating in a final project that pulls all new skills together.
- Responsible Insights: Understand the ethical, security, and operational nuances of AI, helping to navigate potential pitfalls with confidence.
Course description for study year 2025-2026. Please note that changes may occur.
Course code
E-MBA140
Version
1
Credits (ECTS)
10
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English
Content
Topics include:
- Introduction to AI and Business Intelligence
- Data analytics with AI
- Data-driven decision-making with AI
- Using AI as a synthetic information source
- Incorporating behavioral economics insights
- Ethical and responsible use of AI
Learning outcome
Participants will gain the following knowledge and skills by completing the course.
Knowledge
- Basic Understanding: Discuss the fundamental design, capabilities, and practical applications of large language models in data-driven business contexts.
- Data-Driven Frameworks: Describe the core methods and frameworks used in AI-driven data analytics.
- Ethical Considerations: Evaluate ethical considerations and responsibilities in AI deployment.
Skills
- AI-Driven Data Skills: Handle both structured and unstructured data (e.g., text).
- AI-Enhanced Analytical Skills: Analyze diverse data sets using AI-based solutions, including text-, network, and regression analyses.
- Survey & A/B Testing Design: Apply AI to structure surveys, gauge customer willingness to pay, and optimize engagement through iterative testing.
- Behavioral Economics Application: Incorporate key behavioral economics principles to better understand customer motivations and design interventions that enhance recruitment and retention.
- Using AI as a Synthetic Information Source: Employ AI tools for market analysis, persona creation, focus group simulations, and product testing to inform data-driven product ideation and development.
- Ethical & Responsible AI Use: Recognize AI-driven processes' potential biases, security concerns, and privacy implications.
- Capstone Project Proficiency: Integrate the core course materials to develop, analyze, and present a comprehensive, data-driven business plan.
Required prerequisite knowledge
Exam
Continous assessment and Final project
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Continous assessment | 1/5 | Letter grades | ||
| Final project | 4/5 | Letter grades |
Continuous assessment is Quizzes and mini assignments throughout the semester.In the Final project, Participants design and execute a project addressing a real-world business challenge using data-based Generative AI techniques and submit a written report.