Industry placement
Build the skills to start your career as an AI engineer at leading technology companies.
- Practical projects with industrial partners
- Internships at technology companies
I°Bachelor's programme
First-cycle studies in Artificial Intelligence
A seven-semester first-cycle programme taught in Polish, educating computer science engineers with broad computing knowledge and extended mathematical foundations needed in artificial intelligence.
For candidates who want strong computer science, mathematical, and engineering preparation for designing AI-based solutions.
- Degree
- Bachelor of Engineering
- Duration
- 3.5 years · 7 semesters
- Language
- Polish
- Seats
- 64 seats
Programme structure
Rigorous foundations with room to specialise.
This seven-semester, Polish-taught bachelor's programme develops broad computer science skills and the mathematical foundations needed to design artificial intelligence systems.
2,500 hours of theoretical and practical classes in total.
Core subjects
Solid mathematical and computer science foundations, plus key AI areas:
- Computer architecture and organisation
- Programming languages and algorithms
- Computer networks and cybersecurity
- Databases and data warehouses
- Machine learning
- Deep learning
Elective subjects
Deepen your expertise in selected AI applications:
- Image processing
- Big data processing
- Natural language processing
- Generative models
- Representation learning
Graduate profile
Graduates of the bachelor's programme are prepared to:
1
Defining problems, acquiring data, and designing AI-based solutions
2
Designing, training, and deploying AI models
3
Analyzing and processing multimodal, complex, and large-scale data
4
Estimating resources and designing infrastructure for AI solutions
5
Understanding business, ethical, legal, and social aspects of AI
6
Rapid adaptation to evolving AI knowledge and tools
7
Soft skills: interdisciplinary teamwork, presenting solutions, design thinking
Development paths
Your future with AI @ PWr.
Further study
Solid foundations prepare you for a master's degree and further specialisation.
- Join research projects at the university
- Prepare for an academic career
Your own projects
Develop your own ideas through team projects and the engineering thesis.
- Mentoring from experienced researchers and practitioners
- Access to labs and compute resources
Curriculum
The curriculum, semester by semester.
Semester 1
I
Mathematical analysis for computer scientists 1
7 ECTS
Algebra for computer scientists
5 ECTS
Logic for computer scientists
4 ECTS
Programming
8 ECTS
Introduction to artificial intelligence
4 ECTS
Introduction to studying artificial intelligence
2 ECTS
Semester 2
II
Mathematical analysis for computer scientists 2
5 ECTS
Coding and abstract algebra
2 ECTS
Discrete mathematics
5 ECTS
Computer architecture
4 ECTS
Algorithms and data structures
4 ECTS
Machine learning
5 ECTS
Programming paradigms
5 ECTS
Physical education
Semester 3
III
Data management systems
5 ECTS
Operating systems and high-performance computing
5 ECTS
Deep learning
6 ECTS
Individual research-and-deployment project 1
1 ECTS
Foreign language 1
3 ECTS
Introduction to probability and measure theory
5 ECTS
Foundations of computation and learning theory
5 ECTS
Physical education
Semester 4
IV
Advanced artificial intelligence methods
4 ECTS
Rapid AI prototyping 1
4 ECTS
Deployment and maintenance of AI-based solutions 1
4 ECTS
Individual research-and-deployment project 2
1 ECTS
Foreign language 2
3 ECTS
Complex networks
4 ECTS
Probability with elements of stochastic processes
6 ECTS
Cryptography and information security
4 ECTS
Semester 5
V
Creative problem-solving methods
2 ECTS
Social responsibility
1 ECTS
Artificial intelligence development trends
2 ECTS
Rapid AI prototyping 2
4 ECTS
Deployment and maintenance of AI-based solutions 2
4 ECTS
Individual research-and-deployment project 3
1 ECTS
Statistics with elements of information theory
7 ECTS
Elective course from Block 1
5 ECTS
Elective course from Block 2
4 ECTS
Elective course from Block 2
4 ECTS
Semester 6
VI
AI team project 1
3 ECTS
Industry placement
6 ECTS
Legal, social and ethical aspects of artificial intelligence
2 ECTS
Elective course from Block 1
5 ECTS
Elective course from Block 1
5 ECTS
Elective course from Block 1
5 ECTS
Elective course from Block 2
2 ECTS
Elective course from Block 2
2 ECTS
Semester 7
VII
AI team project 2
20 ECTS
Foundations of business and innovation
4 ECTS
Elective course from Block 2
2 ECTS
Elective course from Block 2
2 ECTS
Elective course from Block 2
2 ECTS
Elective block Blok 1
Blok 1
Explainable and trustworthy AI systems
5 ECTS
AI security
5 ECTS
Metaheuristics
5 ECTS
Natural language processing
5 ECTS
Image processing
5 ECTS
Audio processing and analysis
5 ECTS
Big data processing
5 ECTS
Biometrics
5 ECTS
Generative artificial intelligence models
5 ECTS
New trends in algorithmics
5 ECTS
Wearable biometric data processing
5 ECTS
Elective block Blok 2
Blok 2
Controlled generation techniques in generative models
2 ECTS
Data visualization and interpersonal communication
2 ECTS
Representation learning
2 ECTS
Distributed infrastructure
2 ECTS
Social media processing
2 ECTS
Distributed ledger technology - blockchain
2 ECTS
Efficient artificial intelligence methods
2 ECTS
Affective computing
2 ECTS
Responsible artificial intelligence
2 ECTS
Recommender systems and personalization
2 ECTS
Complex data processing
2 ECTS
Brain-computer interfaces
2 ECTS
Data collection techniques and challenges
2 ECTS
After graduation
Where the degree can take you.
AI EngineerML EngineerDS EngineerML OpsAI OpsData Engineer
The official programme notes growing demand for designers and programmers of AI-based solutions, including AI Engineer, ML Engineer, DS Engineer, ML Ops, AI Ops, and Data Engineer roles.
Apply
Apply through the IRK system
Current dates and requirements are listed in the Wrocław University of Science and Technology recruitment system.