Abdyreshit Sadyk

About Me

I am currently a university student studying Technologies of Digital Economy with a strong focus on data science, artificial intelligence, and computational technologies. My academic journey is driven by curiosity about how data can be used to understand complex systems and improve decision-making.
I am particularly interested in the intersection of machine learning, neuroscience, and biomedical signal analysis. My research interests include Brain-Computer Interfaces (BCI), electroencephalography (EEG) data analysis, and the application of artificial intelligence in diagnosing neurological conditions.
Beyond my academic research, I continuously develop practical skills in programming, data analysis, and machine learning. I enjoy working on innovative projects that combine software development, intelligent systems, and scientific experimentation.
My long-term goal is to contribute to advanced research and technological innovation in artificial intelligence and data science while collaborating with international teams and organizations.

MY SKILLS

Programming

Python
R
HTML, CSS
JavaScript

Neurotechnology

EEG Signal Processing
ADS1299 Data Acquisition
BCI System Architecture
Signal Filtration

Hardware & Integration

Raspberry Pi / GPIO
Gemini API Deployment
Edge Computing
System Latency Optimization

Data Science

Python (Pandas, Scikit-learn)
Predictive Modeling
Time-Series Forecasting
Statistical Analysis

Machine Learning

Linear Regression
Random Forest Classifier
Supervised/Unsupervised Learning

Tools

Git
GitHub
Streamlit

MY PROJECTS

The following portfolio projects delineate my technical contributions and academic research across the domains of neurotechnology, computational data science, and digital systems architecture. Each project represents a synthesis of theoretical frameworks and practical application.

S&P500 Market Analysis

This project involves developing a machine learning application to analyze and predict the performance of the S&P 500 stock market index.

Language: Python
Libraries: Pandas (data manipulation), Scikit-learn (machine learning), and Yfinance (financial data).

Learn more

Notebooks on Data Science

This repository serves as a centralized portfolio for various data science implementations, primarily focusing on predictive analytics and machine learning applications. While it functions as a collection of different analytical tasks, the core objective is to demonstrate the end-to-end data science pipeline—from data ingestion to model evaluation.