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Welcome to my GitHub repository! Here you will find a collection of projects that showcase my expertise as a data scientist, highlighting my skills in Python, R, SQL, Power BI, and statistical analysis. I hold a bachelor’s degree in Actuarial Science, providing a solid foundation in mathematical modeling and risk assessment.
I am a dedicated and passionate data scientist, constantly exploring complex data sets to extract meaningful insights that drive informed decision-making. With a strong background in statistics, I employ a data-driven approach to tackle real-world problems and deliver innovative solutions.
In this repository, you can expect to find a diverse range of projects that demonstrate my technical proficiency and analytical mindset. From exploratory data analysis to building machine learning models to statistical inference, each project is designed to showcase the practical application of data science techniques.
Python: I leverage the power of Python to wrangle, clean, and transform large datasets. Whether it’s data preprocessing, feature engineering, or model implementation, I utilize Python’s rich ecosystem of libraries such as NumPy, Pandas, and Scikit-learn.
R: R is another powerful tool in my arsenal, particularly when it comes to statistical analysis, data visualization, and creating reproducible research. I utilize R’s extensive libraries like ggplot2, dplyr, and tidyr to uncover patterns and trends in the data.
SQL: Proficient in SQL, I can effectively query databases and perform data manipulation tasks. I utilize SQL to extract relevant information, join tables, and aggregate data for analysis.
Power BI: I specialize in creating interactive and visually appealing dashboards using Power BI. These dashboards provide an intuitive way to communicate complex insights and facilitate data-driven decision-making.
Statistics: With a solid foundation in statistics, I employ a range of statistical techniques, including hypothesis testing, regression analysis, and time series forecasting, to uncover patterns and derive meaningful insights from data.
I’m always eager to connect with fellow data enthusiasts, industry professionals, and researchers. Please feel free to reach out if you have any questions, project proposals, or simply want to discuss the latest developments in data science.
Welcome to my GitHub repository! Here you will find a collection of projects that showcase my expertise as a data scientist, highlighting my skills in Python, R, SQL, Power BI, and statistical analysis. I hold a bachelor’s degree in Actuarial Science, providing a solid foundation in mathematical modeling and risk assessment.
I am a dedicated and passionate data scientist, constantly exploring complex data sets to extract meaningful insights that drive informed decision-making. With a strong background in statistics, I employ a data-driven approach to tackle real-world problems and deliver innovative solutions.
In this repository, you can expect to find a diverse range of projects that demonstrate my technical proficiency and analytical mindset. From exploratory data analysis to building machine learning models to statistical inference, each project is designed to showcase the practical application of data science techniques.
Python: I leverage the power of Python to wrangle, clean, and transform large datasets. Whether it’s data preprocessing, feature engineering, or model implementation, I utilize Python’s rich ecosystem of libraries such as NumPy, Pandas, and Scikit-learn.
R: R is another powerful tool in my arsenal, particularly when it comes to statistical analysis, data visualization, and creating reproducible research. I utilize R’s extensive libraries like ggplot2, dplyr, and tidyr to uncover patterns and trends in the data.
SQL: Proficient in SQL, I can effectively query databases and perform data manipulation tasks. I utilize SQL to extract relevant information, join tables, and aggregate data for analysis.
Power BI: I specialize in creating interactive and visually appealing dashboards using Power BI. These dashboards provide an intuitive way to communicate complex insights and facilitate data-driven decision-making.
Statistics: With a solid foundation in statistics, I employ a range of statistical techniques, including hypothesis testing, regression analysis, and time series forecasting, to uncover patterns and derive meaningful insights from data.
I’m always eager to connect with fellow data enthusiasts, industry professionals, and researchers. Please feel free to reach out if you have any questions, project proposals, or simply want to discuss the latest developments in data science.
Let’s collaborate and leverage the power of data science to drive innovation and create a brighter future together!
04c2347 (First Commit on Kubuntu)