MBA Artificial Intelligence and Data Science

MBA in AI & Data Science curriculum consists of the following topics: AI analysis, solution design, implementation and agile project management. The programme merges academic theory with practical skills, preparing graduates for leadership positions in the dynamic tech industry.

(400 hours) – Foundations & Design

• Analyse AI Needs and Formulate Tailored Solutions (198 hrs):
  This module builds foundational AI knowledge through descriptive statistics, modelling, and ML fundamentals while aligning AI feasibility with business needs. It covers process mapping, data quality, GDPR, and risk analysis, supported by workshops in data visualisation and requirement formalisation.

• Design an AI Solution (209 hrs):
  This module focuses on data pipelines and AI design, covering ETL/ELT processes, data cleansing, and big data tools like data lakes and warehouses. It deepens understanding of machine learning and deep learning models, including neural networks and reinforcement learning. Practical workshops involve TensorFlow, data mining, and evaluating AI performance for real-world implementation.

• Innovation & Professional Development (83 hrs):
  Emphasises creativity, quantum computing awareness, ethical AI practices and career portfolio development.

(450 hours) – Execution & Leadership

• Manage IT Projects with Agility and Stakeholders (124 hrs):
  This module covers project management techniques, including both traditional and Agile methods, with workshops on AI project breakdown, specifications, and organisation. It also focuses on team management in multicultural and remote environments, with workshops on leading, collaborating, and supporting teams across cultures, including disability management and building resilience.

• Transversal Skills (85 hrs):
  This involves workshops exploring open innovation projects and emerging technologies like quantum computing to encourage creativity and industry readiness.

Extracurricular Professional Pathway (5 hrs):
This module involves preparing a professional report with individual follow-ups and group discussions. It provides guidance on report writing and culminates in a professional report defence, allowing students to showcase their research and analysis.