Warsaw University
of Technology

Faculty of Electronics
and Information Technology

Students

WEITI » Students »

The Faculty Library

Visit us at the Faculty Library!

The Library is located in Room 40 (ground floor).


Opening hours of The Faculty Library during Summer holidays:
1 July - 29 August: Monday - Friday 9 am - 2 pm
In July & August READING ROOMS ARE CLOSED!



*******

THE CENTRAL CATALOGUE OF WUT LIBRARIES»

*******

EMPLOYEES
Library Director-Custodian Olga Bogatek, M.A.	tel. 22 234 7625 e-mail olga.bogatek@pw.edu.pl
Senior Librarian Anna Gątarek, M.A.	tel. 22 234 7625 e-mail anna.gatarek@pw.edu.pl
Librarian Małgorzata Rymut	tel. 22 234 7625 e-mail malgorzata.rymut@pw.edu.pl
Senior Librarian Kamila Szlaga, M.A.	tel. 22 234 7625 e-mail kamila.szlaga@pw.edu.pl
Senior Librarian Anna Zaręba, M.A.	tel. 22 234 7625 e-mail anna.zareba@pw.edu.pl

RULES AND REGULATIONS

Regulations of the Library and Information System of WUT (pdf, 371.17 kB)

Contact us

tel. (+48 22) 234-76-25
tel. (+48 22) 234-58-32
e-mail bwepw.elka@pw.edu.pl

ul. Nowowiejska 15/19, room 40
00-665 Warszawa

New books in the Library

	Crepalde N. Big data on Kubernetes. A practical guide to building efficient and scalable data solutions Packt Publishing, 2024 Description: Big data on Kubernetes. A practical guide to building efficient and scalable data solutions (msword, 29.00 kB)
	Vijayakumaran S. DevOps. Frameworks, techniques, and tools Rheinwerk Publishing, 2024 Description: DevOps. Frameworks, techniques, and tools (msword, 29.00 kB)
	Bustos J.P., Lopez Soria L. Generative AI application integration patterns. Integrate large language models into your applications Packt Publishing, 2024 Description: Generative AI application integration patterns. Integrate large language models into your applications (msword, 30.00 kB)
	Kolodiazhnyi K. Hands-on machine learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines. Second edition Packt Publishing, 2025 Description: Hands-on machine learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines. Second edition (msword, 30.00 kB)
	Liu M. Learn generative AI with PyTorch Manning, 2024 Description: Learn generative AI with PyTorch (msword, 30.50 kB)
	Romano F., Kruger H. Learn Python programming. A comprehensive, up-to-date, and definitive guide to learning Python. Fourth edition Packt Publishing, 2024 Description: Learn Python programming. A comprehensive, up-to-date, and definitive guide to learning Python. Fourth edition (msword, 28.50 kB)
	Abhishek K., Abdelaziz M. Machine learning for imbalanced data. Tackle imbalanced datasets using machine learning and deep learning techniques Packt Publishing, 2023 Description: Machine learning for imbalanced data. Tackle imbalanced datasets using machine learning and deep learning techniques (msword, 29.50 kB)
	Ozdemir S. Quick start guide to large language models. Strategies and best practices for ChatGPT, embeddings, fine-tuning, and multimodal AI. Second edition Addison-Wesley, 2024 Description: Quick start guide to large language models. Strategies and best practices for ChatGPT, embeddings, fine-tuning, and multimodal AI. Second edition (msword, 29.50 kB)
	Bourne K. Unlocking data with generative AI and RAG. Enhance generative AI systems by integrating internal data with large language models using RAG Packt Publishing, 2024 Description: Unlocking data with generative AI and RAG. Enhance generative AI systems by integrating internal data with large language models using RAG (msword, 29.50 kB)