AI in industry and business 2.5 credits

The course is aimed at working professionals in industry and business, who wish to gain knowledge of artificial intelligence (AI) and its use in organizations. The course covers the theoretical foundations of AI, including an overview of how both fundamental and modern AI techniques work. Building on this knowledge, the course then moves on to cover applications of AI in industry and business, covering different domains and giving examples such as using pre-trained AI components to automate administrative tasks and how an organization can utilize their own data to build AI models. Here, both technical and organizational prerequisites for AI adoption will be discussed, with special focus on digitalization, data management and AI governance. Finally, the course will give participants insights into issues on ethics and security of AI in industry and business.

Course Contents

The course is aimed at working professionals in industry and business, who wish to gain knowledge of artificial intelligence (AI) and its use in organizations. The course covers the theoretical foundations of AI, including an overview of how both fundamental and modern AI techniques work. Building on this knowledge, the course then moves on to cover applications of AI in industry and business, covering different domains and giving examples such as using pre-trained AI components to automate administrative tasks and how an organization can utilize their own data to build AI models. Here, both technical and organizational prerequisites for AI adoption will be discussed, with special focus on digitalization, data management and AI governance. Finally, the course will give participants insights into issues on ethics and security of AI in industry and business. The course includes the following elements: - Theoretical foundations of AI - Overview of modern AI techniques, including deep learning (DL) and large language models (LLMs) - AI capabilities and AI applications in business and industry - Retrieval-Augmented Generation (RAG) and AI automation of administrative workflows - AI readiness: organizational and technical prerequisites for AI, with special focus on data management and AI governance - AI security and ethics, such as privacy and confidentiality issues

Prerequisites

Passed courses of at least 40 credits in a main field of study within Engineering and Technology, Natural Science or Social Sciences, and at least 1 year of work experience (or equivalent). English proficiency is required (level 6 or equivalent). Applicants that have at least 4 years of work experience in industry are exempt from the requirement of at least 40 credits within Engineering and Technology, Natural Science or Social Sciences field.

Selection

Level of Education: Second cycle

Coursecode/Ladok code: T2AFFO

The course is conducted at: School of Engineering

Label Value
Study type Distance learning
Number of required meetings 0
Semester Autumn 2025
Study period week 38 - week 43
Rate of study 25%
Language English
Location Web-based
Time Mixed-time
Tuition fees do NOT apply for EU/EEA citizens or exchange students 7125 SEK
Application code HJ-13185