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ME2317 Artificial Intelligence and Management 6.0 credits

Information per course offering

Termin

Information for Spring 2026 Start 16 Mar 2026 programme students

Course location

KTH Campus

Duration
16 Mar 2026 - 1 Jun 2026
Periods
P4 (6.0 hp)
Pace of study

33%

Application code

60417

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

10 - 50

Target group

Open for all programs as long as it can be included in your programme

Planned modular schedule
[object Object]
Schedule
Schedule is not published
Part of programme
No information inserted

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus ME2317 (Autumn 2025–)
Headings with content from the Course syllabus ME2317 (Autumn 2025–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Artificial intelligence (AI) is transforming the world, helping organisations of all sizes to grow, innovate and make smarter decisions. This course aims to provide students with knowledge of the principles, tools and techniques that drive this transformation. The course provides an understanding of AI and machine learning and its applications in various business areas and industry sectors.

The course provides an introduction to AI and machine learning, focusing on techniques, theories and historical development. It emphasises the central role of data, from collection to analysis, and explores the potential of AI in business and industrial applications. The course analyses the strengths and weaknesses of AI and identifies specific problem areas where AI can be useful, both in industry and society.

Furthermore, the course addresses AI from a strategic business perspective, emphasising the integration of AI into business strategies, and balancing efficiency with adaptability. Ethical, legal and regulatory aspects of AI are discussed, as well as business risks. The course concludes with a practical case where participants identify suitable business areas for AI and implement a strategy to apply AI to specific problem areas.

The course consists of five modules:

1. Basic AI,

2. Business applications of AI,

3. Strategic AI,

4. Ethics, laws and regulations in relation to AI,

5. Implementation of an AI strategy.

Intended learning outcomes

After passing the course, the student shall be able to:

1. Explain the theoretical foundations and historical development of artificial intelligence (AI) and machine learning,

2. Identify and apply AI techniques to specific business problems and identify relevant problem areas in industry, society and businesses where AI can create value,

3. Explain how AI can be integrated into companies' business strategies and analyse different processes for AI implementation,

4. Identify and discuss ethical considerations and analyse legal and regulatory aspects of AI to ensure ethically and legally sustainable AI applications,

5. Formulate an implementation strategy for an AI application customised to a specific business area.

Literature and preparations

Specific prerequisites

Fulfilled the requirements for a Degree of Bachelor in technology, natural sciences or mathematics.

English B/English 6, or the equivalent.

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • INL1 - Assignment, 1.0 credits, grading scale: P, F
  • KON1 - Partial exam, 2.0 credits, grading scale: A, B, C, D, E, FX, F
  • PRO1 - Project, 3.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Industrial Management

Education cycle

Second cycle