Course syllabus

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TRA235 TRA235 Data-driven product realization lp2 HT24 (7.5 hp)

Course is offered by the department of Tracks

Contact details

Examiner:
Jon Bokrantz, PhD
Assistant Professor
Department of Industrial and Materials Science
Division of Production Systems
E-mail: jon.bokrantz@chalmers.se
Phone: 031-772 36 14

Co-developer:
Anders Skoogh, PhD
Full Professor
Department of Industrial and Materials Science
Division of Production Systems
E-mail: anders.skoogh@chalmers.se
Phone: 031-772 48 06

Course purpose

The aim of the course is to provide a platform to work and solve challenging cross-disciplinary authentic problems from different stakeholders in society such as the academy, industry or public institutions. Additionally, the aim is that students from different educational programs practice working efficiently in global multidisciplinary development teams.
The demand for future engineers with multi-disciplinary competencies in developing and applying AL/ML solutions in industry has skyrocketed. Therefore, the course aims to provide students with fundamental knowledge about data science (including AI and ML) as well as skills in applying data science techniques for improving production systems and product development.

Schedule

TimeEdit

Course literature

The literature includes lecture materials (PowerPoint presentations, available on the Canvas course homepage) and scientific articles (available from Chalmers Library or Canvas course homepage). See details in the course PM available on Canvas.

Course design

The course follows a project-based learning pedagogy and consists of a mix of Teaching and Learning Activities (TLAs):

  • Lecture: Theoretical knowledge, skills, and abilities needed for the project work.
  • Community: Expert talks to get inspiration from state-of-the-art data analytics applications, combined with paper seminars, self-paced learning modules, and shared reflections.
  • Project: Practical work focused on the achievement of data-driven and fact-based decisions in the industrial product realization process.
  • Examination: Assessment activities that constitute the basis for the final grade.

The course is structured according to the Cross-Industry Standard for Process Mining (CRISP-DM) model, which is a systematic approach for planning, executing, and deploying data analytics projects. The course includes 8 major phases with the following content:

 

Phase 1 – Course Introduction & Project Introduction

  • Course and project introduction
  • Data Science in Product Realization
  • CRISP-DM

Phase 2 – Business Understanding

  • Project management
  • Roles and responsibilities
  • Problem-solution mapping

Phase 3 – Data Understanding

  • Methods for pre-processing
  • Self-paced learning (intercultural communication)

Phase 4 – Data Preparation

  • Data quality

Phase 5 – Modeling

  • Real data sets from industry projects
  • Self-paced learning (ethics)

Phase 6 – Evaluation

  • Model Evaluation & Business Impact

Phase 7 – Deployment

  • Model deployment
  • Operation and Maintenance

Phase 8 – Report & Presentation

  • Presentation seminar
  • Self-studies
  • Hand-in of final report

 

Learning objectives

After successful completion of the course, the student should be able to:

 

LO1. Critically and creatively identify and formulate data analytics problems

LO2. Solve open-ended data analytics problems

LO3. Lead and participate in data analytics projects

LO4. Work in multidisciplinary analytics teams

LO5. Work sensitively with cultural differences in analytics teams

LO6. Assess the impact of data analytics solutions

LO7. Identify and discuss ethical aspects of data analytics

LO8. Present the results of data analytics project to various stakeholders

 

Link to the syllabus on Studieportalen.

https://www.chalmers.se/en/education/your-studies/find-course-and-programme-syllabi/course-syllabus/TRA235/?acYear=2024/2025

Examination form

The course examination is based on three parts: (1) project work, (2) individual quiz, and (3) individual reflection. The final grade includes the students’ performance on all three parts, and all three parts are mandatory and must be approved separately to pass the course.

 

The project work covers the entire process from initial project formulation to the final presentation and report (see practical details under the heading “Project work”). The report constitutes the main basis for grading the project work. The individual quiz covers the content presented during lectures, community, and literature. The quiz will be conducted as an online knowledge test in Canvas. The individual reflection covers the student’s ability for in-depth reflection on success factors experienced during the project work.

 

The final grade includes the students’ performance on all three assessment tasks:

  • Project report and seminar: maximum 60 points.
  • Individual quiz: maximum 25 points.
  • Individual reflection: maximum 15 points.

 

Grades are individual. The grading scale is Failed, 3, 4, and 5. All points are summarized, and the final grade is decided accordingly (the total sum cannot surpass 100):

0-49     points = Fail

50-64   points = 3 (and all assessment tasks must be separately approved)

65-84   points = 4

85-100 points = 5

 

Student representatives

All Chalmers courses have student representatives who are expected to take part in a start-up meeting, one meeting in the middle of the course, and the final course evaluation meeting in the study period after the course where thoughts and impressions about the course are shared. The course representatives for TRA235 have been randomly selected and consist of:

Jansu Ali jansua@student.chalmers.se
Filip Bergom bergom@student.chalmers.se
Kirill Durkin durkin@student.chalmers.se
Johannes Johansson johut@student.chalmers.se
Jianing Lei jianingl@student.chalmers.se

Course summary:

Date Details Due