UIINP00003 Building AI

Faculty of Philosophy and Science in Opava
Summer 2024
Extent and Intensity
0/2/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. Ing. Petr Sosík, Dr. (seminar tutor)
doc. Mgr. Petr Suchánek, Ph.D. (assistant)
Guaranteed by
doc. Ing. Petr Sosík, Dr.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Supplier department: Institute of Computer Science – Faculty of Philosophy and Science in Opava
Timetable of Seminar Groups
UIINP00003/A: Wed 8:55–10:30 B2, P. Sosík
UIINP00003/B: Tue 20. 2. 15:35–16:20 MS, P. Suchánek
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Building AI is a flexible online course for anyone who wants to learn about the practical methods that make artificial intelligence a reality. You will get a solid introduction to for example machine learning and neural networks, and you will learn where and how AI methods are applied in real life. It is easy to move freely between the three difficulty levels, from multiple choice exercises to programming with Python – depending on whether you know programming or not. As a result of this course, you will be able to craft your own AI idea and present it to the community.
Learning outcomes
Upon completing the course, students will gain a comprehensive understanding of artificial intelligence concepts and applications. They will learn to identify and solve real-world problems using AI, understand the ethical implications of AI, and develop skills in programming and data analysis. The course also covers machine learning techniques, neural networks, and the basics of AI project management. By the end, students will be equipped to apply AI tools and methodologies in various domains, enhancing their problem-solving capabilities and preparing them for advanced AI studies or careers
Syllabus
  • 1. Getting started with AI 2. Dealing with uncertainty 3. Machine learning 4. Neural networks 5. Conclusion
Literature
  • Link to the course: https://buildingai.elementsofai.com/
Teaching methods
Interactive online course
Assessment methods
Online exercises. You must complete at least 19 exercises (out of a total of 21) and answer 50% of them correctly. Each exercise has three difficulty options (beginner, intermediate and advanced). Completion of any of these levels counts as completion of the exercise. Intermediate and advanced tasks require programming. If you complete a sufficient number of intermediate or advanced exercises, this will be noted on your certificate of completion.
Language of instruction
English
Further comments (probably available only in Czech)
Study Materials
Information on completion of the course: IMPORTANT: to get credits, you must register to the course by your university email.
The course can also be completed outside the examination period.
General note: Credits will be granted two times per year, after Jan 31 and Jul 31.
Teacher's information
https://buildingai.elementsofai.com/
The course is available in English (https://buildingai.elementsofai.com/). The course certificate is charged, and if interested, the student can request and pay for it individually. It is not necessary to present a certificate to get credits. The only condition for granting credits is the fulfillment of the course requirements. Credits will be awarded during the exam period in February and August. !!! The necessary condition is the registration of students in this course with their school email (domain slu.cz)!!!
The course is also listed under the following terms Summer 2025.
  • Enrolment Statistics (recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2024/UIINP00003