30 Computer Science and IT Management Summer Course Programs

Introduction to the fundamental concepts of computer systems. Explores how computer systems execute programs and manipulate data, working from the C programming language down to the microprocessor.

Our AI & Computer Science program covers a wide range of profession-related subjects that are not commonly taught in universities, giving you a competitive edge in the real world. You will learn from experienced professionals and have the opportunity to work alongside them during your internship, gaining invaluable industry experience.

Introduction to the fundamental concepts of computer systems. Explores how computer systems execute programs and manipulate data, working from the C programming language down to the microprocessor.

Topics include counting and combinatorics, random variables, conditional probability, independence, distributions, expectations, point estimation, and limit theorems. Applications of probability in computer science including machine learning and the use of probability in the analysis of algorithms. Prerequisites: 103, 106B or X, multivariate calculus at the level of MATH 51 or CME 100 or equivalent.

Covers advanced programming techniques and data structures. Topics include recursion, algorithm analysis, linked lists, stacks, queues, trees, graphs, tables, searching, and sorting. Students must register for two sections: lecture and laboratory.

Representation, analysis, techniques, and principles for manipulation of basic combinatoric structures used in computer science. Rigorous reasoning is emphasized.

Our Summer School aims at developing the students’ academic knowledge and professional skills in 2 major topics related to Computer Science – Visual computing and Artificial intelligence. You will be involved in various projects with the teaching staff and you will take courses in Visual Computing and Artificial Intelligence, which will provide you with the tools to create virtual reality, video games, virtual divides, interactive objects and to learn about optimizations methods and data mining. As an additional module, French as a Foreign Language will be included to help you socialize with the French population.

Would you like to spend four unforgettable weeks at the number one private higher education institution in Croatia, mastering the latest digital trends in an international environment with students from all over the world? The summer sunshine is the perfect ingredient to get inspired and master cutting-edge innovations from the digital world. Join the International Summer School program at Algebra Bernays University and gain in-demand digital skills that top global tech companies are looking for — all while having an unforgettable summer experience in Croatia.

The application of Newton's Laws to solve 2-D and 3-D static and dynamic problems, particle and rigid body dynamics, freebody diagrams, and equations of motion, with application to mechanical, biomechanical, and aerospace systems. Computer numerical solution and dynamic response.

The Summer School "Beyond 5G: Enabling Technologies, Opportunities and Research Challenges Ahead" is organized to offer 6 ECTS (48 hours of front lessons) in the broad field of 5G and beyond 5G (B5G) networks, targeting an audience of Bachelor (last year), Master and PhD students, early stage researchers and practitioners from Academia or Industry. The technologies, opportunities and research challenges of 5G networks will be presented and discussed during the school.

The 2026 edition of the Summer School Enabling Technologies for Industrial Internet of Things (ET-I2oT 2026) is organized to provide 6 ECTS (about 52 hours of front lessons) in the fields of Electronics, RFID, Sensors, Networking, Web of Things, SW for IoT, Computer Engineering, targeting on one side an audience of Bachelor (last year), Master and PhD students, and on the other side early stage researchers and practitioners from Academia or Industry. Both HW and SW aspects of IoT will be presented and discussed during the school.

Worst and average case analysis. Recurrences and asymptotics. Efficient algorithms for sorting, searching, and selection. Data structures: binary search trees, heaps, hash tables. Algorithm design techniques: divide-and-conquer, dynamic programming, greedy algorithms, amortized analysis, and randomization. Algorithms for fundamental graph problems: minimum-cost spanning tree, connected components, topological sort, and shortest paths. Possible additional topics: network flow, and string searching. Prerequisite: 103 or 103B; 109 or STATS 116.

Introduction to design and development of full-stack web applications. Topics include asynchronous programming; non-relational data stores; use of APIs; serverless (cloud-based) applications; decoupled client/server architectures; performance; testing; packaging; and deployment.

Artificial intelligence has been a fascinating concept for more than a decade, and we are finally getting close to making AI a reality. We are currently witnessing significant innovations in various technologies that all relate to the influence of AI. This drives demand for understanding not only how to use and implement such technologies but also how the basic concepts of selected components really work.

Focuses on understanding the challenges innovators and adopters of technologies face at various stages of technology maturity, the tools and strategic choices organizations have at their disposal, exemplified across a range of technologies.