Юрій

Bubelnyk Yura
Adress: Chervonoyi Kalyny Ave, 78 Lviv
Mobile: [відкрити контакти](див. вище в блоці «контактна інформація»);
e-mail: [відкрити контакти](див. вище в блоці «контактна інформація»)
GitHub: github.com/Yachiry1

Education:
General secondary education (with honors)
Mykolaiv Gymnasium of the Mykolaiv City Council, Stryi District, Lviv Region

Majoring in Computer Technology, Bachelor of AI (2024 - up to now)
Lviv Polytechnic National
University, Stepana Bandera Street 12, Lviv

GENERAL EXPERIENCE AND ACHIEVMENTS
I am a motivated and results-oriented student with a passion for Artificial Intelligence and Data Science. I am capable of working in a team environment and solving problems collaboratively. I continuously strive to enhance both my technical and soft skills, including communication, teamwork, and time management, through active participation in academic and real-world projects.
My primary goal is to deepen my knowledge in machine learning, data analysis, and software engineering by contributing to meaningful projects and internships. I am seeking internship or trainee positions at forward-thinking IT companies where I can gain hands-on experience, build professional networks, and grow into a confident junior specialist.

Skills:
Programming & Software Engineering:
• Solid foundation in Python, C++, and Java.
• Knowledge of object-oriented programming (OOP) principles and design patterns.
• Experience with Git, GitHub, Docker (basic usage, Dockerfiles, containers), and modern development environments (VSCode, IntelliJ, etc.)

Algorithmic Thinking & Problem Solving:
• Strong skills in data structures (arrays, stacks, queues, trees, graphs) and common algorithms (searching, sorting, recursion, dynamic programming).
• Practice with platforms like LeetCode, AlgoTester, and Codeforces to improve algorithmic efficiency.
• Ability to analyze and optimize solutions for complexity and performance.

Data Science & Machine Learning (Beginner Level):
• Familiar with NumPy, Pandas, Matplotlib for data manipulation and visualization.
• Understanding of linear regression, overfitting, and polynomial fitting.
• Working to deepen understanding of gradient descent, loss functions, and model evaluation.

Mathematics & Statistics
• Understanding of linear algebra (matrices, vectors, eigenvalues/eigenvectors), calculus (derivatives, integrals, optimization), and probability theory (Bayes' theorem, conditional probability).
• Basic knowledge of hypothesis testing, statistical distributions, and parameter estimation.

Languages:
Ukrainian (native), English at B2 level (I read documentation, can communicate and write letters).