-ALL-COURSES-

Data Science courses here: https://github.com/TheFebrin/DataScience

Semester 1

• Mathematical Analysis (lecture: Maciej Paluszyński, class: Yuriy Kryakin)

• Logic for Computer Science (lecture: Witold Charatonik, class: Antoni Kościelski)

• Introduction to Programming in C (lecture: Marek Piotrów, workshop: Krystian Bacławski)

• Introduction to Computer Science (lecture: Tomasz Jurdziński, class: Artur Kraska)

• Java course (lecture: Paweł Rzechonek, workshop: Przemysław Gospodarczyk)

Semester 2

• Algebra (lecture: Artur Jeż, class: Witold Karczewski)

• Programming Methodology (lecture: Filip Sieczkowski, Maciej Piróg class: Dariusz Biernacki)

• Object-Oriented Programming (lecture: Marcin Młotkowski, workshop: Robert Kraus)

• English B2-II

Semester 3

• Numerical Analysis (B) (lecture: Paweł Woźny, class: Witold Karczewski)

• Discrete Mathematics (B) (lecture: Katarzyna Paluch, class: Szymon Dudycz)

• Efficient Implementation of Algorithms

• Protection of Intelectual Property (lecture: Julian Jezioro)

• Development of the Enrollment System (workshop: Jan Marcinkowski)

Semester 4

• Algorithms and Data Structures (M) (lecture: Krzysztof Loryś, class: Szymon Dudycz)

• Artificial Intelligence (lecture: Paweł Rychlikowski, class: Paweł Rychlikowski)

• Probability and Statistics (lecture: Witold Karczewski, class: Pratik Ghosal)

• Programming in C++ (lecture: Paweł Rzechonek, workshop: Przemysław Uznański)

• Another View of Economy (lecture: Witold Kwaśnicki)

• Sport Programming in Practice

Semester 5

• Machine Learning (lecture: Jan Chorowski, workshop: Piotr Wieczorek)

• Data Mining (lecture: Piotr Wnuk-Lipiński, class: Piotr Wnuk-Lipiński)

• Selected Areas of Practical Software Development (lecture: Wiktor Zychla, class: Piotr Wieczorek)

• Advanced techniques in C++ and STL (lecture: Paweł Rzechonek, workshop: Paweł Rzechonek)

• Advanced Python Programming (lecture: Marcin Młotkowski, workshop: Adam Kaczmarek)

• Human-Computer Interaction (lecture: Zdzisław Płoski, workshop: Leszek Grocholski)

• Efficient Implementation of Algorithms 2

Semester 6

• Neural Networks and Deep Learning (lecture: Jan Chorowski, class: Paweł Laskoś-Grabowski)

• Evolutionary Algorithms (lecture: Piotr Wnuk-Lipiński, class: Piotr Wnuk-Lipiński)

• Computer Networks (lecture: Marcin Bieńkowski, workshop: Szymon Dudycz)

• Computer Systems (lecture: Piotr Witkowski, workshop: Piotr Polesiuk)

• Data Bases (lecture: Piotr Wieczorek, class: Robert Ferens)

• Workshops: Deep Learning (companies: AlphaMoon, EY, MicroscopeIT, NeuroSys and Tooploox)

Semester 7

• Artificial Intelligence for Games

• Natural Language Processing

• Seminar: Data Mining

Semester 8

• Project: Deep Learning

• Thesis

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Data Science

Semester 1

• Algorithmic Trading

• Numerical Optimization

• Design and Implementation of Systems in the Cloud

• Intelligence Services in State Security System and International Relations

Semester 2

• Statistical learning
• Algorithmic Trading
• Object-oriented Software Development
• Using Convolutional Neural Networks to Analyze 1D, 2D, and 3D Data
• Modern web development

Semester 3

• Modeling financial derivatives using F#
• Statistics and Linear Models
• Conversational bots and question answering
• Algorithmic Causality with Applications