Coding a Self-Driving Car in JavaScriptLaajuus (3 op)
Tunnus: DT10064
Laajuus
3 op
Opetuskieli
- englanti
Vastuuhenkilö
- Radu Mariescu-Istodor
Osaamistavoitteet
- Students will gain an understanding of what artificial intelligence is
- Students will practice solving a real-world problem
- Students will apply fundamental mathematical tools
- Students will be guided to build a complex software system
- Students will extend a given software system according to specifications
- Students will practice modern JavaScript programming techniques
Sisältö
In this course we study how to build a self-driving car simulation using JavaScript. We build every component ourselves, without using any external libraries so that we really understand how a system like this works. We learn how to implement the car driving mechanics, how to define the environment, how to simulate sensors, how to detect collisions and how to make the car control itself using a neural network. We briefly study how biological neural networks work and see how to implement artificial neural networks using code. We also study a basic optimization algorithm for improving the neural network. The entire system is complex, however, each component is relatively easy in and of itself requiring only a good understanding of high-school mathematics/physics and some programming experience (not necessarily JavaScript).
Lisätiedot
Coding exercises in HTML, CSS and (primarily) JavaScript.
Ilmoittautumisaika
01.04.2022 - 14.09.2022
Ajoitus
13.09.2022 - 31.12.2022
Opintopistemäärä
3 op
Virtuaaliosuus
3 op
Toteutustapa
Etäopetus
Yksikkö
Täydentävänosaamisen opinnot (TAYO)
Opetuskielet
- Englanti
Koulutus
- Tietojenkäsittelyn koulutus
Opettaja
- Radu Mariescu-Istodor
Ryhmät
-
KAKS22Karelia, avoin, kaikki, syksy, 2022
-
TOP22_23Täydentävän osaamisen opintojen ryhmä lv 2022-2023
Tavoitteet
- Students will gain an understanding of what artificial intelligence is
- Students will practice solving a real-world problem
- Students will apply fundamental mathematical tools
- Students will be guided to build a complex software system
- Students will extend a given software system according to specifications
- Students will practice modern JavaScript programming techniques
Sisältö
In this course we study how to build a self-driving car simulation using JavaScript. We build every component ourselves, without using any external libraries so that we really understand how a system like this works. We learn how to implement the car driving mechanics, how to define the environment, how to simulate sensors, how to detect collisions and how to make the car control itself using a neural network. We briefly study how biological neural networks work and see how to implement artificial neural networks using code. We also study a basic optimization algorithm for improving the neural network. The entire system is complex, however, each component is relatively easy in and of itself requiring only a good understanding of high-school mathematics/physics and some programming experience (not necessarily JavaScript).
Aika ja paikka
Moodle link: https://moodle.karelia.fi/course/view.php?id=7477
Oppimateriaalit
Video playlist:
https://www.youtube.com/playlist?list=PLB0Tybl0UNfY8T85rlEnL-ohEz2lIKH-6
Opetusmenetelmät
Video lectures and personal feedback on exercises
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
A student must complete a minimum of 6 Assignments to pass the course.
Each Assignment is Pass/Fail and the final grade is formed as follows:
6 Assignments = Grade 1
7 Assignments = Grade 2
8 Assignments = Grade 3
9 Assignments = Grade 4
10 Assignments = Grade 5
Arviointikriteerit, tyydyttävä (1-2)
Student is able to explain at least 50% of the project source code.
Arviointikriteerit, hyvä (3-4)
Student is able to explain over 90% of the project source code. And make improvements to the code.
Arviointikriteerit, kiitettävä (5)
Student completed all exercise tasks perfectly.
Lisätiedot
Coding exercises in HTML, CSS and (primarily) JavaScript.
Ilmoittautumisaika
01.04.2022 - 01.05.2022
Ajoitus
02.05.2022 - 15.08.2022
Opintopistemäärä
3 op
Virtuaaliosuus
3 op
Toteutustapa
Etäopetus
Yksikkö
Tradenomi / Tietojenkäsittely (DD)
Toimipiste
Wärtsilä-kampus Karjalankatu 3 (WÄR)
Opetuskielet
- Englanti
Paikat
20 - 500
Koulutus
- Tietojenkäsittelyn koulutus
Opettaja
- Radu Mariescu-Istodor
Vastuuopettaja
Radu Mariescu-Istodor
Ryhmät
-
KAKK22KEKarelia, avoin, kaikki, kesä, 2022
Tavoitteet
- Students will gain an understanding of what artificial intelligence is
- Students will practice solving a real-world problem
- Students will apply fundamental mathematical tools
- Students will be guided to build a complex software system
- Students will extend a given software system according to specifications
- Students will practice modern JavaScript programming techniques
Sisältö
In this course we study how to build a self-driving car simulation using JavaScript. We build every component ourselves, without using any external libraries so that we really understand how a system like this works. We learn how to implement the car driving mechanics, how to define the environment, how to simulate sensors, how to detect collisions and how to make the car control itself using a neural network. We briefly study how biological neural networks work and see how to implement artificial neural networks using code. We also study a basic optimization algorithm for improving the neural network. The entire system is complex, however, each component is relatively easy in and of itself requiring only a good understanding of high-school mathematics/physics and some programming experience (not necessarily JavaScript).
Aika ja paikka
Course is open from 1.6.2022-15.8.2022 on Moodle:
https://moodle.karelia.fi/course/view.php?id=6911
All assignments have deadline on 1.8.2022.
Grading will follow soon afterwards.
Oppimateriaalit
Material is available on Moodle:
https://moodle.karelia.fi/course/view.php?id=6911
And in this video playlist:
https://www.youtube.com/playlist?list=PLB0Tybl0UNfY8T85rlEnL-ohEz2lIKH-6
Opetusmenetelmät
Video lectures and personal feedback on exercises.
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
A student must complete a minimum of 6 Assignments to pass the course.
Each Assignment is Pass/Fail and the final grade is formed as follows:
6 Assignments = Grade 1
7 Assignments = Grade 2
8 Assignments = Grade 3
9 Assignments = Grade 4
10 Assignments = Grade 5
Arviointikriteerit, tyydyttävä (1-2)
Student is able to explain at least 50% of the project source code.
Arviointikriteerit, hyvä (3-4)
Student is able to explain over 90% of the project source code. And make improvements to the code.
Arviointikriteerit, kiitettävä (5)
Student completed all exercise tasks perfectly.
Lisätiedot
Coding exercises in HTML, CSS and (primarily) JavaScript.