TIES4911 Deep-Learning for Cognitive Computing for Developers (8–10 op)

Opinnon taso:
Syventävät opinnot
Arviointiasteikko:
0-5
Suorituskieli:
englanti
Vastuuorganisaatio:
Informaatioteknologian tiedekunta
Opetussuunnitelmakaudet:
2020-2021, 2021-2022, 2022-2023, 2023-2024

Avainteksti

Huom. Lukuvuodesta 2019-2020 opintojakson laajuus on 8-10 op.

Kuvaus

Arviointiperusteet

More information is available at the course web-page: http://users.jyu.fi/~olkhriye/ties4911

Osaamistavoitteet

By any measure, the past few years have been landmark years for the discussion around Artificial Intelligence and its potential impact on business and society. Being based on Artificial Intelligence, Cognitive Computing Systems are "systems that learn at scale, reason with purpose and interact with humans naturally". Cognitive Computing solutions encompass Machine Learning, Reasoning, Natural Language Processing, Deep Learning, Speech and Vision, Human-Computer Interaction and more. The course aims to provide practical view to the domain of Cognitive Computing and Machine Intelligence. Sstudents will learn how to build Machine Intelligence based solutions using corresponding open-source software libraries (e.g. TensorFlow). At the same time, students will be capable to design and build own services and apps using cloud-based Cognitive Services of such big competing player in this field as IBM, Google, Microsoft, etc. 

Lisätietoja

Esitietojen kuvaus

There are no specific requirements. However, the course is practical and requires at least basic skills in programming (Python is the main programming languages of the course). It would be easier to follow the course having at least a basic knowledge of SOA and Cloud Computing, Data Mining, Artificial Intelligence, Knowledge Engineering and Natural Language Processing.

Oppimateriaalit

All the study related materials are available from the course web-page: http://users.jyu.fi/~olkhriye/ties4911

Suoritustavat

Tapa 1

Kuvaus:
Completion of 100% course tasks (given during the lectures and demo sessions) brings 8 credits. Extra 2 credits will be given for completion of optional Mini Project.
Arviointiperusteet:
Final evaluation is based on evaluations of the tasks given during the lectures and demo sessions. Task specific evaluation criteria are mentioned in corresponding task description.
Valitaan kaikki merkityt osat
Suoritustapojen osat
x

Completion of course tasks/assignments (8–10 op)

Tyyppi:
Itsenäinen työskentely
Arviointiasteikko:
0-5
Arviointiperusteet:
Final evaluation is based on evaluations of the tasks given during the lectures and demo sessions. Task specific evaluation criteria are mentioned in corresponding task description.
Suorituskieli:
englanti
Työskentelytavat:

Lectures and Demo Sessions. Assignments/tasks to be completed individualy and in groups.

Oppimateriaalit:

Lecture materials are available from the course webpage.

Opetus