Amanatullah Pandu Zenklinov

Headed the Statistics Undergraduate Programme, overseeing curriculum development aligned with industry standards in Data Science, AI/ML/DL, and Machine Learning in Production. Conducted classes, mentored students, and managed program operations including scheduling, budgeting, and accreditation.

Prepared lecture schedules and developed curriculum with supporting documents for the Statistics Department. Monitored academic activities, conducted evaluations, and implemented follow-up actions for continuous quality enhancement.

Prepared and presented engaging lecture materials on data science, statistics, machine learning, and deep learning, incorporating practical examples and assignments. Assisted students in mastering R and Python programming, statistical analysis, data visualization, and SQL for database management.

Managed approximately 100 projects in data analysis, data science, machine learning, and AI systems, including Chatbot LLM. Developed tailored AI/ML models, optimized model performance, and engineered personalized recommendation systems.

Improved AI training processes using machine learning and data science knowledge, and clarified complex scientific and coding concepts to enhance model performance. Ensured code validity, effectiveness, and compliance with high academic standards for enterprise software readability.

Performed data entry and verification for financial revenue, ensuring accuracy and reliability of records. Analyzed financial data to identify trends and patterns, supporting informed decision-making processes.

Conducted detailed data verification and accepted the verification process of Party's member population data in compliance with KPUD regulations, ensuring data security. Designed and oversaw an organized database, simplifying data management and improving accessibility.

Assisted in food commodity surveys, collecting accurate data on materials and corn for BPS. Facilitated the analysis of food commodity data to detect trends and insights, supporting decision-making and policy formation.

Actively participated in statistical seminars, workshops, and conferences, enhancing both theoretical knowledge and practical skills in the field, with a focus on Python and R. Excelled in academic projects, demonstrating skills in time series analysis and exploratory data analysis, including techniques requiring graphical visualization for insightful data interpretation and presentation. Complete

Activities and societies: Actively participated in student organizations and volunteering initiatives, demonstrating leadership skills and a commitment to community engagement through statistical applications.

Actively participated in student organizations and volunteering initiatives, demonstrating leadership skills and a commitment to community engagement through statistical applications. Excelled in academic project, demonstrating skills in data mining, data structures, and their implementation using SQL, including proficient querying, database design, and optimization techniques for efficient data r

Demonstrated proficiency in conducting research by devising an innovative approach for scaling a previously thought non-scalable community detection algorithm, published in a peer-reviewed journal. Excelled in academic project, demonstrating skills in algorithm design, data structures, and machine learning. Completed highly demanding coursework in Statistical Process Control, Econometrics, Inferen