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Intelligent System Applications (ISA_I) Foundations of Generative AI and Applied Machine Learning @ FIIT STU in Bratislava

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#  Intelligent System Applications (ISA_I)
- Aplikácie inteligentných systémov

## Foundations of Generative AI and Applied Machine Learning
- Neural Recommender Systems
- Machine Learning Systems
- Privacy-Preserving Machine Learning
 
By completing the course, students will gain knowledge about the development and deployment of real-world intelligent system applications. Through lectures, exercises and projects, students will cover the theory, practical knowledge of **foundation of generative AI** and skills that underpin **applied machine learning** in terms of building **intelligent system applications** with respect to **data protection**. The educational outcomes will provide students with the opportunity to enhance their understanding of machine learning specifics in application domains like e-commerce, monitoring systems, and remote sensing. Working on individual projects will encourage students to come up with their own ideas for implementing intelligent applications in both the **development** and **deployment** phases.

- Data and generative foundation of models
- Responsible AI, production-ready application design
- Practical use cases of Applied ML: RecSys, AI-Assisted systems, ML systems

### [Lectures](https://github.com/FIIT-ISA/ISA-course/tree/main/lectures)

### [Exercises](https://github.com/FIIT-ISA/ISA-course/tree/main/exercises)

### [Course conditions](https://github.com/FIIT-ISA/ISA-course/blob/main/condition.md)

### MS Teams

### Course textbook / Base literature

- NGUYEN, G., LYTVYN, O., 2026. **Foundations of Generative AI and Applied Machine Learning**. Spektrum STU Publishing, ISBN 978-80-227-5556-6, DOI 10.61544/VUEV8972, University Textbook Series, 2026. Available at FIIT STU e-library [ ELVIRA ](https://elvira.fiit.stuba.sk/) with AIS access.

### Recommended literature

- ZHANG A., et al., 2023: [Dive into Deep Learning](https://d2l.ai/index.html), Cambridge University Press. ISBN 978-1009389433. Adopted at 500 universities from 70 countries.
 
- HUYEN, C., 2022. [Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications](https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/). O'Reilly Media, Inc. ISBN 978-1098107963.

- AGGARWAL, C.C., 2016. [Recommender Systems](https://link.springer.com/book/10.1007/978-3-319-29659-3). Springer. ISBN 978-3-319-29657-9.

### Notes
Knowledge in the course **[Intelligent Data Analysis (IAU_B) @ FIIT STU](https://github.com/FIIT-IAU/IAU-course)** at the level of a graduate of the Bachelor's study program in Computer Science is assumed.

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