PA015 AI for Software Professionals

Fakulta informatiky
podzim 2025

Předmět se v období podzim 2025 nevypisuje.

Rozsah
2/0/0. 2 kr. (plus ukončení). Ukončení: zk.
Vyučováno kontaktně
Vyučující
doc. RNDr. Tomáš Brázdil, Ph.D., MBA (přednášející)
Garance
doc. RNDr. Tomáš Brázdil, Ph.D., MBA
Katedra strojového učení a zpracování dat – Fakulta informatiky
Dodavatelské pracoviště: Katedra strojového učení a zpracování dat – Fakulta informatiky
Předpoklady
Basic knowledge of software development.
Omezení zápisu do předmětu
Předmět je nabízen i studentům mimo mateřské obory.
Mateřské obory/plány
Cíle předmětu
Artificial intelligence is rapidly transforming all areas of computer science and software development. AI-driven technologies are reshaping how software is engineered, deployed, and managed, impacting fields such as software development, systems administration, data science, and resource management. At the same time, AI introduces new cybersecurity challenges—enhancing threat detection and response while enabling more sophisticated cyberattacks and exposing new vulnerabilities.

This course provides a comprehensive exploration of AI’s role in modern computing, focusing on its practical applications. Students will gain an in-depth understanding of how AI is integrated into software engineering, IT service management, and cybersecurity. The course will cover fundamental AI concepts, including machine learning, deep learning, and natural language processing, while emphasizing real-world applications and case studies.
Výstupy z učení
While providing essential technical background on AI agents and approaches, this course primarily focuses on their real-world implications. We will explore the strengths and limitations of AI, highlighting its data-driven nature and potential biases. By the end of the course, students will be equipped with the knowledge to critically assess AI applications in their respective fields and make informed decisions about AI-driven technologies in software development, IT management, and cybersecurity.
Osnova
  • Machine learning system lifecycle
  • Data: Ingestion, cleaning, preprocessing
  • Machine learning techniques: Short non-technical overview
  • Deployment of AI agents AI in Software Development

    Automated code generation and AI-assisted programming
  • Bug detection and software testing with AI-driven tools
  • AI in DevOps: Continuous integration and deployment (CI/CD) automation
  • Predictive analytics for software performance and maintenance

    Intelligent system monitoring and self-healing infrastructure
  • AI-driven cloud and resource optimization
  • AI in IT service management (AIOps)
  • AI for network administration and traffic management

    Machine learning for anomaly detection and threat intelligence
  • AI-powered fraud detection and authentication security
  • Adversarial AI and emerging security risks
  • Ethical considerations and AI governance in cybersecurity
Výukové metody
Lectures, homework assignments
Metody hodnocení
Written exam.
Vyučovací jazyk
Angličtina
Další komentáře
Předmět je vyučován každoročně.
Výuka probíhá každý týden.
  • Permalink: https://is.muni.cz/predmet/fi/podzim2025/PA015