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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. 01

    Defining problems, acquiring data, and designing AI-based solutions

  2. 02

    Designing, training, and deploying AI models

  3. 03

    Analyzing and processing multimodal, complex, and large-scale data

  4. 04

    Estimating resources and designing infrastructure for AI solutions

  5. 05

    Understanding business, ethical, legal, and social aspects of AI

  6. 06

    Rapid adaptation to evolving AI knowledge and tools

  7. 07

    Soft skills: interdisciplinary teamwork, presenting solutions, design thinking

Development paths

Your future with AI @ PWr.

  1. 01

    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

  2. 02

    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

  3. 03

    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

30ECTS

  • 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

30ECTS

  • 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

30ECTS

  • 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

30ECTS

  • 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

34ECTS

  • 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

30ECTS

  • 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

30ECTS

  • 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.

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.

  • AI Engineer
  • ML Engineer
  • DS Engineer
  • ML Ops
  • AI Ops
  • Data Engineer

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Current dates and requirements are listed in the Wrocław University of Science and Technology recruitment system.

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