LET-REMA-LC1902
Text and Multimedia Research Project
Course infoSchedule
Course moduleLET-REMA-LC1902
Credits (ECTS)3
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Arts; Graduate School;
Lecturer(s)
Coordinator
prof. dr. M.A. Larson
Other course modules lecturer
Lecturer
prof. dr. M.A. Larson
Other course modules lecturer
Contactperson for the course
prof. dr. M.A. Larson
Other course modules lecturer
Examiner
prof. dr. M.A. Larson
Other course modules lecturer
Academic year2023
Period
PER 1  (04/09/2023 to 05/11/2023)
Starting block
PER 1
Course mode
full-time
Remarks-
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims
● Develop expertise and gain experience in a new research area.
● Build skills in solving real world problems related to text and multimedia data.
● Practice carrying out scientific research.
● Learn to apply best practices of data science and machine learning.
Content
In this course, you carry out an independent project related to artificial intelligence (AI) algorithms (or systems) that analyze text, speech, audio, images or video. The emphasis is on AI that extracts meaning from content, including natural language processing, speech recognition, and computer vision. You may choose your own project topic, but it must be approved by the instructor. You are encouraged to choose a topic that is related to the security of AI systems or the privacy implications of AI algorithms. The project topic must be well-motivated, feasible, and distinct from the topics of other past projects that you have carried out, or future projects that you are planning. The goal of this course is for you to expand your expertise into a new research area and further build your ability to solve real-world problems and carry out scientific research. You will gain experience in applying best practices of data science and machine learning and awareness of the importance of security and privacy in the intersection of language, meaning, and AI. Note that this is a "skills" course, but the skills that you learn will be largely dependent on the nature of the project that you choose. After this course, you will have a keen awareness of how to make sure that you are working to solve a problem or answer a question, rather than merely running algorithms on data.  
Level

Presumed foreknowledge

Test information

Specifics

Instructional modes
Lecture

Tests
Paper
Test weight100
Test typeProject
OpportunitiesBlock PER 1, Block PER 1

Minimum grade
5,5