Methods and technologies of artificial intelligence

Lecture 1.Introduction to Artificial Intelligence

Lecture 2. History of AI development

Lecture 3. Areas of AI application

Lecture 4. Machine learning – fundamentals

Lecture 5. Types of learning (supervised, unsupervised, reinforcement learning)

Lecture 6. Concepts of machine learning

Lecture 7. Machine learning algorithms

Lecture 8. Fundamentals of Deep Learning

Lecture 9. Infrastructure and ecosystem of artificial intelligence

Lecture 10. The future and ethics of AI

 

The Structure and Evolution of Stars

Lecture 1. Thermodynamic Equilibrium

Lecture 2. Star Formation. Fragmentation

Lecture 3. Protostars

Lecture 4. Young Stars

Lecture 5. Hydrogen Burning

Lecture 6. Zero-Age Main Sequence (ZAMS) Stars

Lecture 7. Post-AGB Stars

Lecture 8. White Dwarfs

Lecture 9. Evolution of Stars with Masses Greater than 15 Solar Masses

Lecture 10. Evolution of Stars with Masses Greater than 60 Solar Masses

 

Intelligent data processing systems

Lecture 1. Intelligent information systems: architecture and principles of operation

Lecture 2. Expert systems: structure and areas of application

Lecture 3. Genetic algorithms and evolutionary methods for finding solutions

Lecture 4. Artificial neural networks in intelligent data processingYoung Stars

Lecture 5. Kohonen self-organizing maps: theory and application

Lecture 6. Architecture of modern server systems and computing clusters

Lecture 7. Server network technologies: Ethernet, InfiniBand and topologies from the TOP-500 list

Lecture 8. Internal structure of server nodes and principles of their scaling

Lecture 9. Virtualization and hypervisors: combining operating systems and workstations

Lecture 10. Data storage technologies: distributed systems and security