Fundamentals of Deep Learning (5 op)

Aika ja paikka

Course can be done in own pace in TechClass environment.

Oppimateriaalit

Online.

Harjoittelu- ja työelämäyhteistyö

N/A

Tenttien ajankohdat ja uusintamahdollisuudet

Online.

Kansainvälisyys

N/A

Toteutuksen valinnaiset suoritustavat

N/A

Arviointimenetelmät ja arvioinnin perusteet

Exercises 50%
Quizzes 25%
Project 25%

Opiskelijan ajankäyttö ja kuormitus

Lectures = 40h
Exercises = 15h
Self-study = 40h
Quizzes = 10h
Project = 30h
Total = 135 hours

Sisällön jaksotus

Up to student her-/himself.

Opetusmenetelmät

100% online Self-Study course.

- Tutorial Videos
- Exercises
- Quiz
- Project
- Self-study

Arviointiasteikko

Hyväksytty/Hylätty

Arviointikriteerit, tyydyttävä (1)

- The student knows the basic definitions of Deep Learning.
- The student knows the general difference between Machine Learning and Deep Learning.
- The student knows the primary types of Deep Learning methods.
- The student is familiar with the concept of mapping that learning algorithms perform.
- The student is familiar with variations of Neural Network algorithms used for different applications.

Arviointikriteerit, hyvä (3)

- The student is familiar with basic concepts of the Neural Network algorithm such as wight and neuron.
- The student knows the reasons for the advent of Deep Learning and its history.
- The student knows the intuitions behind Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).
- The student is familiar with the steps of training and evaluating Neural Networks.
- The student knows the applications of CNNs and RNNs.

Arviointikriteerit, kiitettävä (5)

- The student understands the concepts and intuitions behind the Neural Network algorithm.
- The student knows the concepts of regularization, overfitting, and hyperparameters selection.
- The student knows layers of CNNs.
- The student is familiar with the popular architectures of CNNs.