AIS1001 - Introduction to Mechatronics


This course is no longer taught and is only available for examination.

Examination arrangement

Examination arrangement: Oral Examination
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Oral Examination 100/100

Course content

The course contains the following topics:

  • Microcontrollers with components and architecture.
  • Introduction to digital technology, logic, combinatorics and number systems.
  • Introduction to electronics.
  • Introduction to measurement engineering, signal processing and statistics.
  • Introduction to imperative (procedural) programming.
  • Introduction to project work and lab work with an emphasis on best practice.

Learning outcome


  • The candidate is familiar with the use of microcontrollers as a central device within IoT and automation and can describe typical components and architecture, application areas, strengths and limitations.
  • The candidate can explain fundamental theory, methods and relationships of digital design, logic, combinatorics, and number systems.
  • The candidate understands the difference between alternating current (ac) and direct current (dc), and can describe qualitatively and quantitatively fundamental aspects of electronics, such as components (e.g., conductor, resistance, condensator, inductor, diode), transformers, energy sources, circuits, sensors (e.g., temperature, light or sound sensors), and actuators (e.g., dc motor or stepper motor).
  • The candidate can describe application areas, advantages and limitations with basic methods for measurements and signal processing, including measurement errors, sampling, the sampling theorem, and aliasing.
  • The candidate can explain the imperative programming paradigm and fundamental programming concepts, and do a simple comparison with other paradigms (e.g., object-oriented programming or functional programming).


  • The candidate can convert analog and digital signal, convert between number systems, and use and analyse logic and combinatorical circuits.
  • The candidate can read and understand circuit diagrams and schematics, including connecting circuits from specifications, and analysing such circuits using Ohm's law and Kirchhoff's laws.
  • The candidate can perform measurements with multimeter, oscilloscope, and sensors; perform simple signal processing and analysis (e.g., sampling, filtering, time response), and control stepper motors or the speed of dc motors using H-bridge or pulse width modulated outputs.
  • The candidate can implement imperative computer programs that use data types, control structures, loops, functions, state machines, and libraries; analyse program flow; and write programs that are easy to read, expand, maintain, and well documented.
  • The candidate can design and construct simple cyber-physical systems consisting of microcontrollers, sensors, actuators, circuits, and components.

General competence

  • The candidate can use interdisciplinary knowledge for designing simple systems consisting of software, hardware, and electronics, which together perform some desired task.
  • The candidate can perform simple testing and error detection in systems of subsystems
  • The candidate is aware with relation to safety during lab work and can handle components and lab equipment in a safe manner

Learning methods and activities

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.

Further on evaluation

The final grade is based on an overall evaluation of the portfolio, which consists of a number of works delivered through the semester. The portfolio contains assignments that are carried out, digitally documented and submitted during the term. Both individual and team assignments may be given. Assignments are designed to help students achieve specific course learning outcomes, and formative feedback is given during the period of the portfolio. The re-sit exam is an oral exam.

Specific conditions

Admission to a programme of study is required:
Automation and Intelligent Systems (BIAIS)

Required previous knowledge

The course has no prerequisites. It is a requirement that students are enrolled in the study programme to which the course belongs.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester and will typically also include English material.

Credit reductions

Course code Reduction From To
IE100212 10.0 AUTUMN 2022
AIS1104 7.5 AUTUMN 2023
More on the course



Version: 1
Credits:  10.0 SP
Study level: Foundation courses, level I


Language of instruction: Norwegian

Location: Ålesund

Subject area(s)
  • Applied Electrical Engineering
  • Multidisciplinary Electrical Engineering
  • Engineering Cybernetics
  • Engineering
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of ICT and Natural Sciences


Examination arrangement: Oral Examination

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Oral Examination (1) 100/100 2023-12-08
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.
  • 1) Siste gangs eksamen

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

More on examinations at NTNU