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Education and Training

• Bachelor’s Degree in Information Technology
  Technical University of Moldova (UTM)
  Field of study: Information and Communication Technologies
  Level in EQF: EQF level 6

• Certificate of Completion – Excalibur AI Camp
  Sigmoid

  • Fundamental concepts of Artificial Intelligence and Machine Learning
  • Practical implementation of AI algorithms using Python
  • Development of intelligent systems and basic neural networks
  • Applied problem-solving using supervised and unsupervised learning
  • Introduction to key AI libraries such as NumPy, Pandas, Scikit-learn
  • Hands-on projects and teamwork in real-world AI scenarios

Projects

• Sentiment Analysis Web Application
  This project is a Sentiment Analysis Web Application that predicts the sentiment of a given text (positive, neutral, or negative). It consists of two main parts:

  1. Backend: A Flask-based API that handles text processing, sentiment prediction using a deep learning model (Keras/TensorFlow), and TF-IDF vectorization for text features.
  2. Frontend: A React-based web interface where users can input text and receive sentiment analysis results from the backend.

• Dating App
  Developed an AI-powered dating application designed to match users based on personal traits and preferences. The project includes a user profile system, compatibility matching algorithms (including collaborative filtering and sentiment analysis), and a simple interface for interaction. Implemented using Python (pandas, scikit-learn), with a focus on data processing, recommendation systems, and user experience.

• Florist Shop
  Designed and implemented a console-based application for managing a florist shop using Object-Oriented Programming in C++. The system handles flower inventory, promotional strategies, customer interactions, and discount mechanisms. Focused on applying OOP principles such as inheritance, polymorphism, operator overloading, and encapsulation to simulate a real-world store environment.

• Android App
  Developed an Android application that integrates with the Metropolitan Museum of Art public API to display a collection of artworks. The app features a search bar for finding objects by keyword and a local database for managing a personalized list of favorite items. Built using Java and Android Studio, the project demonstrates skills in RESTful API integration, RecyclerView usage, local data persistence, and clean UI design.

Language Skills

• Mother tongue(s): Romanian
• Other language(s):
  • English: B2
  • Italian: A2
  • Russian: A2

Skills

• Python (computer programming)
• Microsoft Office
• C++
• Frameworks & Libraries: OpenCV, Sci-kit learn, NumPy, Pandas, SciPy, Matplotlib.
• Git
• Data Science | Data Collection, Data Processing, Data Analysis, Data Visualisation
• ML (computer programming)
• Implement front-end website design
• Algorithms
• Cooperate with colleagues
• Think analytically
• Solve problems.