Bachelor's degree, first cycle programme, Computer Science

NA On Campus Bachelors Program

University of Warsaw

Program Overview

The Bachelor of Science in Computer Science at the University of Warsaw is a full-time, first-cycle program that builds a strong foundation in programming, algorithms, and computational thinking, ideal for students passionate about technology who want to turn ideas into real-world solutions. You'll gain practical skills in software development, data handling, and complex problem-solving, preparing you for exciting careers in tech while studying at one of Poland's top universities.

### Curriculum structure
Year 1
In your first year, you'll dive into the essentials of computer science, starting with Introduction to Computer Science I (1000-111bWI1a), where you'll explore algorithms, computer anatomy, operating systems, and basic programming in languages like C, including data types, loops, and functions. You'll also tackle Introductory Programming (1000-211bWPI), mastering core constructs like control statements, functions, and data representation while applying math to real computing tasks through labs and exams. Courses like Mathematical Analysis for Computer Science I (1000-211bAM1) round it out, giving you the analytical tools to succeed from day one.

Year 2
Building momentum, year two focuses on deeper programming and logic, with Logics for Computer Scientists (1000-217bLOG) teaching you formal reasoning essential for software design and verification. You'll advance in algorithms and structures, honing skills to analyze complexity and optimize code for efficiency. This year strengthens your ability to handle mid-level challenges, setting a solid base for advanced topics.

Year 3
By your final year, you're ready for cutting-edge applications like Computational Complexity (1000-218bZO), where you'll model problems with Turing machines, circuits, and classes like P, NP, and PSPACE, plus design algorithms and prove hardness. Electives such as High-Performance Computing for Artificial Intelligence (4010-HPA-OG) introduce HPC tools, machine learning basics, time series analysis, and simulations for AI. You'll wrap up with a capstone, applying everything to innovative projects that showcase your expertise.

Focus areas
Core strengths include algorithms and complexity, programming paradigms, mathematical foundations, logics, high-performance computing, and AI applications—perfect for specializing in software engineering, data science, or emerging tech.

Learning outcomes
Graduates possess theory-based knowledge of programming, algorithms, complexity, and math; skills to formulate problems mathematically, design algorithms in models like Turing machines, analyze data formats, and understand paradigms; plus the ability to tackle computational tasks with precision.

Professional alignment (accreditation)
The program aligns with EU standards for first-cycle Computer Science, delivered through the Faculty of Mathematics, Informatics and Mechanics, ensuring rigorous, industry-relevant training.

Reputation (employability rankings)
University of Warsaw's Computer Science program is highly regarded in Poland, with strong employability from its math-computer science integration; official stats highlight top placements in tech firms, though specific QS rankings for the BSc emphasize regional leadership in STEM.

[Official program link](https://informatorects.uw.edu.pl/en/programmes-all/IN/S1-INF/)

Experiential Learning (Research, Projects, Internships etc.)

At the University of Warsaw's Bachelor of Science in Computer Science, you'll dive into hands-on learning right from the start, building real-world skills through labs and projects that mirror industry challenges. Courses like Practical Distributed Systems let you create and expand your own distributed system step-by-step, tackling big data processing, containerization, and scalable infrastructure—skills employers crave. You'll work with cutting-edge tools for machine learning support in large-scale environments and gain expertise in designing reliable, high-traffic systems.

This practical focus shines through in specific program elements like these:
- Laboratories for building distributed systems: Hands-on labs where you incrementally develop a full system to handle large traffic, including reliability engineering and complexity analysis of distributed algorithms.
- Containerization and monitoring tools: Learn to create containerized apps, configure Kafka clusters for communication, set up central logging, and monitor server metrics in distributed setups.
- Big data and MapReduce skills: Implement data stream processing apps that scale dynamically, select non-relational databases, and express problems using the MapReduce paradigm.
- Group and team projects: Collaborate on designing large-scale architectures, making trade-off decisions, diagnosing bottlenecks, and team-based exercises across related courses open to Computer Science students.
- Advanced software and libraries: Use Java for reflection, annotations, classloaders, and dynamic proxies; plus libraries for reinforcement learning and high-performance data processing.
- Interdisciplinary labs and field elements: Access b-learning labs (including some outdoor and e-learning) for stats tools, organism ID apps, and hypothesis testing, available to BSc Computer Science students.

These experiences prepare you to hit the ground running after graduation—apply today to join us! For the full facilities list, check [https://informatorects.uw.edu.pl/en/courses/](https://informatorects.uw.edu.pl/en/courses/".

Progression & Future Opportunities

At the University of Warsaw's Bachelor of Science in Computer Science program, you'll dive into hands-on experiential learning right from the start, building real-world skills through labs and projects that mirror industry challenges. Courses like Practical Distributed Systems let you create and expand your own distributed system step-by-step, tackling big data processing, containerization, and scalable infrastructure—skills employers crave. You'll work with cutting-edge tools and get plenty of practice in team settings, designing reliable systems and optimizing algorithms for large-scale environments.

Here's how our program equips you with practical expertise:
- Laboratories for building distributed systems: Hands-on labs where you incrementally develop a full system to handle massive traffic, learning reliability engineering, containerization (e.g., Docker-like tools), and monitoring infrastructure health.
- Specific software and tools: Configure Kafka clusters for data streaming, implement MapReduce algorithms for big data, set up central logging and resource metrics collection, and work with non-relational databases for scalable apps.
- Group projects and team skills: Collaborative work on system architecture design, bottleneck diagnosis, and dynamic scaling of data-processing applications, plus emphasis on teamwork in courses tied to Computer Science.
- Advanced programming practices: Courses like Advanced Java cover reflection, annotations, classloaders, and dynamic proxies, giving you deep skills in Java for real applications.
- Interdisciplinary practical elements: Opportunities in related electives like debating or complex systems analysis to hone communication and interdisciplinary problem-solving, directly linked to the BSc Computer Science program.

This kind of targeted, practical training sets our graduates up for success—imagine applying to top tech roles with a portfolio of actual systems you've built. Ready to take the next step? Check out the full course and facilities details here: [University of Warsaw ECTS Course Catalogue](https://informatorects.uw.edu.pl/en/courses/). Apply today and let's get you started!