“The course combined relevant theory with real industrial cases, making it both insightful and practically applicable. The participant-driven approach created learning that was directly linked to our own challenges.”
Bojan Cesto, Volvo Cars
Lifelong Learning for Professionals
The School of Engineering offers different competence development alternatives for professionals. Courses that is possible to combine with a professional work-life.
Listed below you find upcoming courses and main areas for competence development.
Current courses
Design and Analysis of Experiments, 2.5 credits, JTH
Design and Analysis of Experiments, 2.5 credits
Data-Driven Process Improvement through Design of Experiments
Do you want to make more confident, data-driven decisions and systematically improve manufacturing processes? This course provides practical tools to plan, conduct, and analyse experiments in real industrial environments. By working with statistical thinking and modern approaches to Design of Experiments, you will learn how to identify the factors that influence quality, performance, and variation – and how to optimise them in a structured and efficient way.
The course is designed for professionals in production, quality, process development, and R&D who want to strengthen their ability to use data as a basis for improvement. The focus is on industrial applications, particularly within metal manufacturing, where sound analysis can support more stable processes, better use of resources, and well-grounded decisions.
After completing the course, you will have a clear methodology for testing ideas, evaluating results, and driving improvement initiatives based on evidence – skills that are directly applicable in your daily work and valuable for both you and your organisation.
Foundations of Data Driven thinking, 2.5 credits, JTH
Foundations of Data Driven thinking, 2.5 credits
Unlock the value of your manufacturing data with the Foundations of Data-Driven Thinking.
This course targets a wide range of roles in industry and the public sector, such as decision-makers, engineering and technical specialists in design and production, and R&D personnel, who seek practical insight into how data-driven AI can be leveraged to create value in their organizations. Working hands-on with real industrial datasets, you’ll learn how to handle common manufacturing data types, such as sensor and time-series data, process and production logs, and quality and test measurements. You will apply methods to:
- assess data quality and readiness (noise, drift, missing values, inconsistencies)
- clean and prepare data for analysis
- perform exploratory data analysis to reveal trends, relationships, and root causes
- visualize and communicate insights in clear, decision-oriented ways.
You’ll also learn how to use the gained insights to plan the next step in an analytics or AI initiative, such as building solutions for predictive maintenance, automated quality inspection, anomaly detection, scrap and yield improvement, process monitoring, or throughput and cycle-time prediction.
Machine Learning and AI in Manufacturing, 2.5 credits, JTH
Machine Learning and AI in Manufacturing, 2.5 credits
Transform manufacturing performance with the power of AI and machine learning.
Machine Learning and AI in Manufacturing Analytics equips professionals with the tools and knowledge to harness predictive modeling, anomaly detection, and explainable AI to improve quality, reduce waste, and optimize industrial processes.
Through hands-on experience with real manufacturing data, participants gain practical expertise in modern machine learning techniques, robust validation methods, and responsible AI practices including transparency, fairness, and risk management.
This course emphasizes the deployment of interpretable, sustainable, and trustworthy AI solutions that enhance decision-making and support the transition toward more efficient, resilient, and data-driven manufacturing system.
Science of Remelting - Aluminium Alloys, 2.5 credits, JTH
Science of Remelting - Aluminium Alloys, 2.5 credits
Drive innovation in aluminium recycling and sustainability!
This course is your gateway to mastering the science behind lightweight, corrosion-resistant, and endlessly recyclable aluminium—an essential material in automotive and aerospace industries. Learn to optimize remelting processes, control impurities with precision, and enhance alloy quality, all while reducing environmental impact. With the growing demand for sustainable, high-quality recycled materials, this course equips you with the skills to lead the way in transforming aluminium production for a greener future.
AI Governance in Practice: Ethics and Responsibility, 5 credits
AI Governance in Practice: Ethics and Responsibility, 5 credits
As AI plays a greater role in business, it is more important than ever to have clear, ethical, and responsible ways to manage the governance routines in organizations. AI Governance in Practice gives you the knowledge you need to handle this fast changing business landscape, covering topics like ethical frameworks, regulatory rules, data management, and new risks in AI. Whether you are leading AI projects, handling compliance, or advising on responsible AI use, this course provides the introductory tools to help you make informed decisions. Read more here. External link, opens in new window.
From AI Opportunity to AI Project, 5 credits
From AI Opportunity to AI Project, 5 credits
Learn how to move from an AI opportunity to an AI project in your organization! This course is designed for professionals who want to move beyond simplistic use of AI and take the next practical step: identifying a relevant opportunity, assessing what is feasible, and shaping a well-founded AI initiative in their own organizational context. The course will equip you with the knowledge and skills to scope an AI project, including how to choose the right problem, understand what is needed to move forward, and develop a structured project proposal that can support real organizational action.
Managing Agentic AI, 5 hp
Managing Agentic AI, 5 credits
Want to understand how agentic AI can create real organizational value and how it can be deployed safely and responsibly? This course offers a practical and strategic introduction to AI agents – systems that can plan, use tools, collaborate, and perform tasks with different levels of autonomy. The course is designed for working professionals who lead or shape AI-enabled work, such as managers, product and process owners, digitalization leaders, and IT, AI, governance, or security stakeholders. You will learn how to identify where agentic AI fits best, how agentic workflows can be designed and evaluated, and what is required in terms of governance, security, data, roles, and change management.
Through lectures, seminars, and project work, you will gain the ability to assess opportunities, risks, and organizational readiness, and to lead the introduction of next-generation AI in practice.
All free-standing courses
See them here!
Courses and activities for professionals at the School of Engineering in the upcoming admissions round.
Here you find all offers for professionals at Jönköping University. Opens in new window.
Competence Development Projects
CIRCUMET Advanced School on Circular Metal Components for the Swedish Manufacturing Industry
Upcoming courses and activities targeting professionals
Click here for all courses at JU for competence development. Opens in new window.
AI Management
Commissioned Education
In addition to the independent courses we offer, directly adapted for professionals and open to everyone to apply, the School of Engineering has many solutions for you who are looking for skills development. Within the framework of commissioned training it is always the employer who orders and pays for your spot.
Contact us so that, in consultation with you and your employer, we can come up with an offer that suits you.
Main areas for competence development
At the School of Engineering you find researchers and teaching staff within following departments.
- Department of Industrial Product Development, Production and Design
- Department of Supply Chain and Operations Management
- Department of Mathematics, Physics and Chemical Engineering
- Department of Computer Science and Informatics
- Department of Materials and Manufacturing
- Department of Construction Engineering and Lighting Science
- Department of Computing
- Project Manager
- School of Engineering
- stefan.brolin@ju.se
- +46 36-10 1717
- Lecturer
- School of Engineering
- madelene.zetterlind@ju.se
- +46 36-10 1531