Sultan Khajidursunogly Email & Phone Number

• Developed an Anomaly Detection System for Time Series Data• Conducted In-Depth Time Series Data Analysis• Designed and Implemented Time Series Forecasting Models:• Fine tuned LLMs for code models• Spearheaded the creation of advanced code models to assist developers in writing efficient and error-free Python code.• Designed and executed rigorous testing procedures, including unit tests, integration tests, and real-world code scenario assessments for code models•… Show more • Developed an Anomaly Detection System for Time Series Data• Conducted In-Depth Time Series Data Analysis• Designed and Implemented Time Series Forecasting Models:• Fine tuned LLMs for code models• Spearheaded the creation of advanced code models to assist developers in writing efficient and error-free Python code.• Designed and executed rigorous testing procedures, including unit tests, integration tests, and real-world code scenario assessments for code models• Developed comprehensive documentation for LLMs(code models), making it easier for developers to understand and utilize these models effectively.• Utilized deep learning techniques and natural language processing (NLP) to train code models that accurately understood and generated Python code snippets. Show less

Remote

• Classical ML: Logistic Regression, Linear Regression, Decision Tree, Gradient Boosting• Deep Learning: Intro to DL, CNN• Reinforcement Learning: Markov Decision Process, Value function, Bellman equation

Астана

Нур-Султан, Казахстан

• Worked on forecasting the values of motion sensor vibrators using Time Series (LSTM, Prophet, ARIMA)• Worked on log anomaly detection for finding malicious users• Made an application for smartphone recognition on an online exam

Нур-Султан, Казахстан

• Data cleaning: Define and determine error types, search and identify error instances, correct the errors, document error instances, and error types, modify data entry procedures to reduce future errors.• Model checking: Manually check accuracy of mapping between physician accounts (NPPES NPI Twitter, RateMD, LinkedIn).• Data labeling: Tagging the data or adding metadata to make it more meaningful and informative. Matching related data from different data sources/sets. Maintaining… Show more • Data cleaning: Define and determine error types, search and identify error instances, correct the errors, document error instances, and error types, modify data entry procedures to reduce future errors.• Model checking: Manually check accuracy of mapping between physician accounts (NPPES NPI Twitter, RateMD, LinkedIn).• Data labeling: Tagging the data or adding metadata to make it more meaningful and informative. Matching related data from different data sources/sets. Maintaining up-to-date information on metadata, changes, and statuses related to each data source Developing accurate, thorough, and timely data reports.• Automation: Connected different Excel files and sheets to continuously monitor changes in statistics. Show less

Master Of Science - Ms, Artificial Intelligence

Bachelor'S Degree, Big Data Analysis, 3.69