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AI & ML for the Business Practitioner (5 cr)

Code: TU00FH43-3001

General information


Enrollment
06.05.2024 - 18.08.2024
Registration for the implementation has ended.
Timing
19.08.2024 - 15.12.2024
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
On-campus
Unit
(2019-2024) School of ICT
Campus
Karaportti 2
Teaching languages
Finnish
Degree programmes
Industrial Management
Teachers
Peter Hjort
Groups
TXQ22SCM
Industrial Management, Supply Chain Management
TXQ22ICT
Industrial Management, ICT Business
TXQ23S2
Tuotantotalouden tutkinto-ohjelma monimuoto
Course
TU00FH43

Implementation has 8 reservations. Total duration of reservations is 24 h 0 min.

Time Topic Location
Mon 19.08.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 26.08.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 02.09.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 09.09.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 16.09.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 23.09.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 30.09.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Mon 07.10.2024 time 17:00 - 20:00
(3 h 0 min)
Tekoäly ja koneoppiminen liiketoiminta-asiantuntijalle TU00FH43-3001
Online
Changes to reservations may be possible.

Objective

The students ability to understand Artificial Intelligence and Machine Learning is developed . The student's potential to work with analytics and reporting tasks are improved.

Content

The course covers different areas of artificial intelligence, so that the main focus is on machine learning. Other areas discussed are e.g. search methods, reinforcement learning and symbolic artificial intelligence. In the machine learning part, the student gets to know both the basic models of machine learning (e.g. linear and logistic regression, clustering) and deep learning and its applications (machine vision, text translation and processing, time series predictions).

Further information

Vapaasti valittava opinto ryhmille TXQ22ICT ja TXQ22SCM. Eitietovaatimuksena on Python-ohjelmoinnin jatkokurssi.

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s central concepts, models and is able to utilize the most common tools. The student understands the criteria and principles of the expertise development.

Assessment criteria, good (3)

Students have achieved the course objectives well, even though the knowledge and skills need improvement in some areas. Students know the course concepts and models well and are able to justify their decisions. The students are able to apply their knowledge in new situations. The student understands the importance of expertise in the field of business and is able to analyze his/her own expertise and areas requiring further development.

Assessment criteria, excellent (5)

Students have achieved the objectives of the course with excellent marks. Students master commendably the course subject area’s concepts, models and tools. Students are able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in new situations. Students are able to analyze the business sector expertise and the evolvement of their own expertise.

Assessment criteria, approved/failed

Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s central concepts, models and is able to utilize the most common tools. The student understands the criteria and principles of the expertise development.

Qualifications

- Basics of Python Programming
- Data management

Additionally the Advanced Python programming course is recommended.

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