Descriptif
Introduction
Have you ever wondered what really lies behind the lyrics of beautifully written, popular song?
Just like a page of fine literature, most songs have secret messages that have been well hidden
behind clever metaphors and colourful similes. Many of the themes from some of the world’s
greatest songs had already been written about more than 2000 years ago by the great Seneca,
and whose works have been translated for modern use. Their complexities have trickled down
throughout time and find themselves into some of our favorite tunes.
Literature of the 17th and 19th centuries is complex, often multi-layered and laboured with pro-
found meaning that are hidden in plain view. With the turning of each page, we delve deeper
and deeper into understanding the wild complexities that involve secrets passions, hidden ambi-
tions, schemes, unrequited love, pain, sorrow, lust, betrayal, grief, heartache, hopelessness and
even UTOPIC JOY! These are the same themes that we find in most well written songs.
This course allows engineering and business students to gain better insight about the music that has
shaped not only pop culture since the 1960s, but also the world in which we live through sometimes
subtle, and sometimes in-your-face challenges to political systems from cold war times until today.
Course Focus
The 17th and 19th Century femmes fatales are the stars of this course. Their plight will be amplified
and made easier to understand through a juxtaposition against must from the late 20th Century up
to the current days of the 21st Century.
In this music appreciation class, we will discover the meaning behind some of the world’s most
iconic anthems. Just like the pages of the finest literature, metaphors are used in the best songs.
Together we will use the tools of academic textual analysis to uncover the mysteries that have al-
ways be visible, but still unseen… But be careful because language, like any living creature is or-
ganic. It evolves, and so do the connotations of it vocabulary. This means that one well placed
word may change your entire interpretation of you read!
effectifs minimal / maximal:
/20Diplôme(s) concerné(s)
- MScT-Double Degree Data and Finance (DDDF)
- MScT-Internet of Things : Innovation and Management Program (IoT)
- MScT-Energy Environment : Science Technology & Management
- MScT-Data and Economics for Public Policy (DEPP)
- MScT-Cybersecurity (CyS)
- MScT-Artificial Intelligence and Advanced Visual Computing
- MScT-Economics for Smart Cities and Climate Policy
- MScT-Environmental Engineering and Sustainability Management
- MScT-Economics, Data Analytics and Corporate Finance
- MScT-Data Science and AI for Business
- MScT-Visual Computing and Creative AI
- MScT-Trust and Responsible AI
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme MScT-Visual Computing and Creative AI
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Trust and Responsible AI
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Internet of Things : Innovation and Management Program (IoT)
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Environmental Engineering and Sustainability Management
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Energy Environment : Science Technology & Management
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Economics for Smart Cities and Climate Policy
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Economics, Data Analytics and Corporate Finance
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
Pour les étudiants du diplôme MScT-Double Degree Data and Finance (DDDF)
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Data Science and AI for Business
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Data and Economics for Public Policy (DEPP)
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Cybersecurity (CyS)
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme MScT-Artificial Intelligence and Advanced Visual Computing
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 1.5 ECTS
La note obtenue rentre dans le calcul de votre GPA.