TIEA389 Introduction to Cognitive Computing (1–3 cr)

Study level:
Intermediate studies
Grading scale:
Pass - fail
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2017-2018, 2018-2019, 2019-2020



For a one (1) credit:
IBM's Cognitive Computing MOOC:
course and lecture diary.

Course outline
Lecture 1: Introduction to IBM Watson
Lecture 2: Deep Question Answering Architecture
Lecture 3: Semantic Integration and Machine Learning
Lecture 4: Natural Language Processing
Lecture 5: UIMA in IBM Watson
Lecture 6: Structured Knowledge in IBM Watson
Lecture 7: Domain Adaptation Methodology
Lecture 8: Distributional Semantics
Epilogue - The Watson Ecosystem and IBM Watson into the Future

For + two (+2) credits
Self / group assignment:
In group: Build up "cognitive computing" application using IBM Bluemix service, make a written report and demonstrate your application on December.

Self: You will have reading material, which explains working principles of Watson Jeopardy application. Based on this material write on essay approx. 10 pages how you build question-answer machine to some existing material. For example:" Turning Stackoverflow to Watson application".

Completion methods

Lecture diary + assigment. (Pass/Fail)

Learning outcomes

After course student will have basic knowledge what kind of tools is needed to build up "Cognitive Computing" system as Watson. If student wants deeper knowledge computational methods behind Watson's working principles following courses are recommended:

- Data mining
- Introduction to feed-forward neural networks
- Signal processing
- Artificial intelligence

Description of prerequisites

Programming 1, Algorithms 1

Completion methods

Method 1

Select all marked parts
Parts of the completion methods

Teaching (1–3 cr)

Participation in teaching
Grading scale:
Pass - fail
No published teaching