PLIN069 Applied Machine Learning Project

Faculty of Arts
Spring 2024
Extent and Intensity
0/0/4. 6 credit(s). Type of Completion: zk (examination).
Taught in person.
Mgr. Marek Grác, Ph.D. (lecturer), Mgr. Dana Hlaváčková, Ph.D. (deputy)
Guaranteed by
Mgr. Richard Holaj, Ph.D.
Department of Czech Language – Faculty of Arts
Contact Person: Bc. Silvie Hulewicz, DiS.
Supplier department: Department of Czech Language – Faculty of Arts
Prerequisites (in Czech)
NOW ( PLIN068 Applied ML )
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 15 student(s).
Current registration and enrolment status: enrolled: 15/15, only registered: 1/15, only registered with preference (fields directly associated with the programme): 0/15
fields of study / plans the course is directly associated with
there are 7 fields of study the course is directly associated with, display
Course objectives
This course will help students to gain practical experience with current ML solutions and technologies through an involvement in a supervised project. The main areas of projects are NLP, image processing and time series forecasting.
Learning outcomes
Student will be able to apply relevant techniques in ML/AI. Student will have the basic knowledge of applying ML/AI in problems where structured data, free text, images or time series forecasting is usable. Student will know how to qualitatively evaluate results using existing metrics.
  • Overview of key notions
  • Setting up project topics
  • Project realization
  • Final student presentation
Teaching methods
Group projects, homework
Assessment methods
Final project and its presentation.
Language of instruction
Further Comments
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2021, Spring 2022, Spring 2023, Spring 2025.
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