course-details-portlet

TPK4186 - Advanced Tools for Performance Engineering

About

Examination arrangement

Examination arrangement: Work
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Work 25/100 A
Work 25/100 A
Work 25/100 A
Work 25/100 A

Course content

This course aims at providing students experience about processing of engineering data and assessment of the performance of complex technical and socio-technical systems. The course relies on computational experiments performed with the scripting language Python and the associated data processing packages (e.g.numpy, panda, and matplotlib).

The course is organized around 4 themes:

Theme 1: Processing of engineering data.

Theme 2: Definition and evaluation of performance indicators.

Theme 3: Automated exploration of design solution spaces.

Theme 4: Use of machine learning techniques for performance optimization.

Learning outcome

Knowledge:

The students should have advanced knowledge on processing of engineering data and assessment of performance indicators of complex technical and socio-technical systems. The students should be able to change formats of data, analyze data, chain engineering tools, and perform specific calculations and simulations.

Skills:

The students shall be able to write large scripts to handle data in various format, to chain automatically the execution of tools, and to perform calculations of performance indicators. They shall be able to structure these scripts in a way they can be maintained and reused.

General competence:

The students shall master a scripting language and use it as a productivity tool in their engineering work. They shall master also the definition and the assessment of performance indicators. They shall be able to report results of experiments in concise and yet complete and informative way.

Learning methods and activities

The course is mainly based on computational experiments. Students are provided with program code that will be modified and extended. The programs will be used for experiements and simulations, and reports with the results shall be sumbitted.

Further on evaluation

Students will be evaluated on the reports they submit. Submission of four reports is mandatory. The grade obtained for each report counts for 25% of the final grade.

By a re-take of an examination all assessments during the course that counts in the final grade have to be re-taken.

Course materials

Antoine Rauzy. Performance Engineering in Python. AltaRica Association. 2020. ISBN 978-82-692273-1-4. pdf available on author's webpages.

Guttag, John. Introduction to Computation and Programming Using Python: With Application to Understanding Data. 2nd ed. MIT Press, 2016. ISBN: 9780262529624. Wes McKinney.

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. O'Reilly Media; 2 edition, 2017, ISBN-13: 978-1491957660 Computer programs presented during the lectures and tutorials.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2025

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Production and Quality Engineering - Production Management
  • Operations Management and Industrial Safety
  • Engineering
  • Production and Quality Engineering
  • Production and Quality Engineering - Information Technology
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Mechanical and Industrial Engineering

Examination

Examination arrangement: Work

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Work 25/100 A
Room Building Number of candidates
Spring ORD Work 25/100 A
Room Building Number of candidates
Spring ORD Work 25/100 A
Room Building Number of candidates
Spring ORD Work 25/100 A
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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