**Responsible professor:** Luc St-Pierre** School:** School of Engineering

# Learning outcomes

Through your studies in Computational Engineering, you will build strong foundations in:

**Applied mathematics:** More specifically, you will advance your competences in integral and differential calculus, linear algebra, statistical analysis and numerical methods.

**Engineering:** You will learn fundamental theories in engineering and use them to solve practical problems in the fields of thermodynamics as well as solid and fluid mechanics.

**Programming and computing:** You will become familiar with the principles of programming, data structures and algorithms. You will also gain experience in using some of the most relevant industrial engineering software packages.

# Curriculum by timing

Orange: basic studies | Green: major studies |

## First year

1st AUTUMN | 1st SPRING |

Differential and Integral Calculus 1 | First Course in Probability and Statistics |

Matrix algebra | Differential and Integral Calculus 2 |

Programming 1 | Differential and Integral Calculus 3 |

Statics and Dynamics | Programming 2 |

Introduction Course for BSc students | Numerical Methods in Engineering |

Introduction to Industrial Engineering and Management | University Wide Studies* |

Compulsory language course | 2nd national lang/Finnish A1 |

*Recommended course: CS-C1000 Introduction to Artificial Intelligence

## Second year

2nd AUTUMN | 2nd SPRING |

Data Structures and Algorithms | Foundations of Continuum Mechanics |

Foundations of Solid Mechanics | Thermodynamics and Heat Transfer |

Basic Course on Fluid Mechanics | Finite Element and Finite Difference Methods |

Materials Science and Engineering | Major optional course |

Computer-aided Tools in Engineering | Elective/ Minor course |

Major optional course | Elective/ Minor course |

## Third year

3rd AUTUMN | 3rd SPRING |

Computational Engineering Project | BSc Thesis and Seminar |

Elective/ Minor course | Elective/ Minor course |

Elective/ Minor course | Elective/ Minor course |

Elective/ Minor course | Elective/ Minor course |

Elective/ Minor course | Elective/ Minor course |

# Curriculum by study modules

## Basic studies

**Code:** ENG3045.A** **

**Extent:** 65 ECTS credits

Code | Course name | ECTS cr | Period |
---|---|---|---|

Mathematics 25 cr: | |||

Differential & integral calculus 1 | 5 | I | |

Matrix algebra | 5 | II | |

First course in probability and statistics | 5 | III | |

Differential & integral calculus 2 | 5 | III | |

Differential & integral calculus 3 | 5 | IV | |

Programming 25 cr: | |||

Programming 1 | 5 | I-II | |

Programming 2 | 5 | IV-V | |

Data structures and algorithms | 5 | I-II | |

Computer-aided tools in engineering | 5 | I-II | |

Numerical methods in engineering | 5 | III | |

General studies 10 cr: | |||

Introduction course for BSc students | 2 | I-V | |

University Wide Studies (recommended course: CS-C1000 Introduction to Artificial Intelligence) | 3 | IV | |

LC-1117 | Compulsory foreign language course | 3 | I-II |

National language requirement (writing test) | 1 | III | |

National language requirement (oral test) | 1 | III | |

Industrial Engineering and management 5 cr: | |||

TU-A1300 | Introduction to Industrial Engineering and Management | 5 | I-II |

## Major: Computational Engineering

**Code:** ENG3082** **

**Extent:** 65 ECTS cr

Code | Course name | ECTS cr | Period |
---|---|---|---|

Compulsory courses, 55 cr: | |||

Statics and dynamics | 5 | II | |

Foundations of Solid Mechanics | 5 | II | |

Foundations of Continuum Mechanics | 5 | V | |

Basic Course on Fluid Mechanics | 5 | I | |

Thermodynamics and Heat Transfer | 5 | III-IV | |

Materials Science and Engineering | 5 | II | |

Finite Element and Finite Difference Methods | 5 | V | |

Computational Engineering project | 10 | I-II | |

JOIN.bsc | BSc thesis and seminar | 10 | III-IV |

Maturity test (completed as part of the BSc thesis seminar) | 0 | ||

Major optional courses, choose 10 cr: | |||

Introduction to Optimization | 5 | IV | |

Statistical & stochastic methods in engineering | 5 | I | |

Foundations of Discrete Mathematics | 5 | IV | |

Stochastic Processes | 5 | II | |

Linear Algebra | 5 | V | |

Partial Differential Equations | 5 | I-II | |

Prediction and time series analysis | 5 | II | |

Electromagnetism | 5 | IV |

In addition, students can include a maximum of 10 credits of practical training (JOIN.trai) in their elective studies.