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Hello, I'm

Nazar Akmyradov

MSc Software Engineer student

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About Me

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I am Nazar Akmyradov, a driven and passionate software engineer currently pursuing an MSc in Software and Service Architecture at Eötvös Loránd University, Hungary. With a strong foundation from my BSc in Computer Science, I have developed significant expertise in back-end and mobile development, particularly with Java and Spring Boot, as well as Android app development.

Throughout my career, I have worked on impactful projects like the Smart House System, where I implemented complex backend logic and data management using RESTful APIs and PostgreSQL, and the Bank Loan Dataset Analysis, which honed my data processing and machine learning skills. These experiences have refined my ability to tackle challenges, think analytically, and deliver efficient solutions.

I am always excited to learn and implement modern technologies, engage in collaborative environments, and contribute to innovative projects that push boundaries. My expertise in Java, Python, and mobile app development, combined with a commitment to continuous learning, makes me an adaptable and effective team player ready to bring value to any software development team.

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Skills

Programming Languages

Java, Python, JavaScript, C

Frameworks & Technologies

Spring Boot, Django, React, Android Studio (Java/Kotlin), RESTful APIs

Data Management & Tools

PostgreSQL, MySQL, Docker, Git

Development Practices

OOP, TDD, Agile Methodologies

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Experience

Android Mobile Developer

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CodeAlpha (Remote) | March 2024 - May 2024

  • Overview: Completed an internship in Android app development.
  • Role: Developed and implemented projects using Android Studio.
  • Technologies: Java, Android Studio, XML.
  • Contributions: Created user interfaces, integrated APIs, optimized app performance.
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Browse My Recent

Projects

Project 1

Smart House System (Software technology lab)

Project 2

Bank Loan Dataset Analysis (Data Science class)

Project 3

Improving Predictive Maintenance for Aircraft Engines Using Hybrid Machine Learning Models (Research Methodology)

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