Course: Programming Language and Artificial Intelligence Technology

« Back
Course title Programming Language and Artificial Intelligence Technology
Course code KFI/PRJD
Organizational form of instruction Seminar
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 8
Language of instruction Czech, English
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Havlík Vladimír, Doc. PhDr. CSc.
Course content
The course is intended for PhD students in the Philosophy and History of Science and Technology program who are expected to demonstrate proficiency in a programming language or artificial intelligence technology as part of their doctoral studies. The content of the course is defined by the course teacher in agreement with the supervisor at the beginning of the semester, based on the programming language or artificial intelligence technology in question and the project to be undertaken.

Learning activities and teaching methods
Seminar
  • Individual project (40) - 76 hours per semester
  • Contact hours - 52 hours per semester
  • Preparation for an examination (30-60) - 80 hours per semester
prerequisite
Knowledge
to explain the basic concepts of statistics and mathematics
to describe the basic principles of computer operation
to explain the basic formats for storing data, especially textual information
Skills
to operate a personal computer at an advanced level
to be proficient in MS Excel spreadsheets
to analyse data and draw conclusions from it
Competences
N/A
N/A
N/A
N/A
learning outcomes
Knowledge
to explain the principles of the selected programming language
to describe the possibilities and advantages of using programming technologies in your research
to understand how a program interacts with the user and verifies the correctness of its function
Skills
to use language control structures and subroutine creation techniques
to prepare, load and process data (text files and common formats - CSV, XML, JSON, etc.)
to visualize and export data read from files or generated by program code into suitable data formats
to use external libraries of the programming language
Competences
N/A
N/A
teaching methods
Knowledge
One-to-One tutorial
Self-study of literature
Individual study
Skills
One-to-One tutorial
Self-study of literature
Individual study
Competences
Self-study of literature
Individual study
One-to-One tutorial
assessment methods
Knowledge
Combined exam
Skills
Combined exam
Competences
Combined exam
Recommended literature
  • Literatura bude stanovena na začátku semestru garantující katedrou. Literature will be determined at the beginning of the semester by the guaranteeing department..


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester