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In the early days of computer science formation, I taught the following courses:
Programming on Assembler Language
Architecture of Computers (IBM 360/370, PC Intel 8-16-, 32-, 64-bit processors, DEC PDP 11, PC Motorola 8-, 16-bit processors)
Operating Systems
Automatic Control Theory
Design of Automated Control Systems
Now I teach courses on:
- Fundamental of Artificial Intelligence. (Basic Models and Methods, bachelor's degree)
Lecture 1. Artificial Intelligence: a historical reference. The A. Turing test
Presentation Lect 1.pdfvidioLecture 1 ukr.mp4Lecture 2. State of the art in Artificial Intelligence
resent_ Lecture 2.pptxvideoLecture 2 ukr.mp4Lecture 3. Knowledge models in Artificial Intelligence. Formal logic. Part 1. Introduction.
Present_ Lecture 3.pdfvideo MMAI Lecture 3.mp4Lecture 4. Formal logic. Part 2. Reasoning in Propositional logic
Present_ Lecture 4.pdfvideoLecture 4.mp4Lecture 5. Formal logic. Predicate logic
Present_ Lecture 5.pdfvideoLecture 5.mp4Lecture 6. Inference in Predicate Logic
Present_ Lecture 6.pdfvideo Lecture 6.mp4Lecture 7-8. Rule-based Systems. Expert Systems
Present_ Lecture 7-8.pdfvideo Lecture 7-8.mp4Lecture 9. Inference in Rule-based Systems
Present_ Lecture 9.pdfvideo Lecture 9.mp4Lecture 10. Uncertainty management in rule-based expert systems. Probabilistic reasoning
Present_ Lecture 10.pdfvideoLecture 10.mp4Lecture 11. Uncertainty management in rule-based expert systems. Certainty factor
Present_ Lecture 11.pdfvideoLecture 11.mp4Lecture 12. Ontology
videoLectu 12.mp4Present_ Lecture 12.pdfLecture 13. Ontology languages. Frames as a knowledge representation technique
Present_ Lecture 13.pdfvideo Lecture 13.mp4Lecture 14. Artificial Neural Network. Introduction
Present_ Lecture 14.pdfvideo Lecture 14.mp4Lecture 15. Multi-Layer Perceptron
Present_ Lecture 15.pdfvideo Lecture 15.mp4Lecture 16. Types of Artificial Neural Networks
Present_ Lecture 16.pdfvideo Lec 16.mp4Lecture 17. Natural Language Processing (NLP)
Present_ Lecture 17.pdfvideo Lec 17.mp4Lecture 18. Machine Learning. Introduction
Present_ Lecture 18.pdfvideoLecture 18.mp4Lecture 19. Machine Learning. Supervised Learning. Introduction
Present_ Lecture 19.pdfvideoLecture 19.mp4Спеціальні питання інформаційних технологій
Спеціальні питання інформаційних технологій
(Intelligent Information Technologies), master's degree, one-semester
Lecture 1. Artificial Intelligence: a historical reference
Presentation Lect 1.pdfvidioLecture 1 ukr.mp4Lecture 2. State of the art in Artificial Intelligence
resent_ Lecture 2.pptxvideoLecture 2 ukr.mp4Lecture 3. Introduction to the Fuzzy Logic System (FLS). Fuzzy Sets
Present_ Lecture 3-1.pdfvideo Lecture 3-1.mp4Present_ Lecture 3-2.pdfvideo Lecture 3-2.mp4Lecture 4. Fuzzy Set Operation and Characteristics
Present_ Lecture 4.pdfvideo Lecture 4.mp4Lecture 5. Fuzzy Relations
Present_ Lecture 5 NURE.pdfvideo Lecture 5 NURE.mp4Lecture 6. Fuzzy Inference
Present_ Lecture 6 NURE.pptxvideo Lecture 6 NURE.mp4Lecture 7. Fuzzy Inference II
Present_ Lecture 7.pdfvideoLecture 7.mp4Lecture 8. Types of Fuzzy Inference Models
Present_ Lecture 8.pdfvideo Lecture 8.mp4Lecture 9. Design of Fuzzy Systems. Part 1
Present_ Lecture II-3.pdfvideoLecture II-3.mp4Lecture 10. Design of Fuzzy Systems. Part 2.
Present_ Lecture II-4.pdfvideo Lecture II-4.mp4Lecture 11. PID control theory
Present_ Lecture 11.pdfvideo Lecture 11.mp4Lecture 12. Design of Fuzzy Systems
Present_ Lecture 12-1.pdfvideo Lecture 12-2.mp4Present_ Lecture 12-2.pdfvideoLecture 12-1.mp4- Neuro-Fuzzy Control in Robotic (bachelor's degree, one semester)
video Lecture 12.mp4Lecture 1.
- Fuzzy Systems (master's degree, one-semester)
Lecture 1.
- Autonomous Intelligent Machines (master's degree, one-semester)
Lecture 1.
- Feeling Artificial Intelligence (PhD degree, one-semester)
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