Hi, I’m Binyameen Khan Afridi
A man with Data Analytic Power
Hello, I'm Binyameen Khan Afridi, a 25-year-old from Peshawar, Pakistan, a passionate data analyst with a strong foundation in programming and a love for the field of data science. My journey began with an interest in programming itself—I was curious about how coding could solve real-world problems, so I set out to learn as much as I could. After diving into Python for a few months, I discovered the vast possibilities in data science and analytics, which sparked my interest even more. Since then, I’ve been building my skills in Python and expanding my knowledge of key libraries like Pandas, NumPy, and Matplotlib for data manipulation and visualization. I've also explored tools and techniques essential for data analysis, including data preprocessing, data wrangling, and building insightful visualizations. With each project, I get to apply my skills to real-world datasets, and I’m always motivated by the chance to uncover patterns and insights that drive impactful decisions. I’m always exploring new techniques and diving deeper into problems to find the best solutions. Some projects take weeks as I experiment, research, and refine my approach to reach optimal results. I even revisit past work, updating code months later when I discover more efficient or effective solutions—this drive for improvement fuels my passion for data science. Through hands-on projects in data analysis and machine learning, I’ve gained practical experience and sharpened my skills. To support my work, I’ve familiarized myself with essential tools, including Git, GitHub, Docker, and testing frameworks, which allow me to develop and manage projects efficiently. I also have a working knowledge of AWS, which enables me to deploy models and applications to the web. Additionally, I’m proficient with Streamlit, which I use to build interactive applications that showcase machine learning models in user-friendly formats.​
My Skills
Programming
Tools
Soft Skill
Programming Language Python
Pandas
NumPy
Scikit-learn
Matplotlib
Seaborn
Streamlit
SQL​​
Power BI
Excel
Git, Github
Jupyter Notebook
Docker
AWS Sagemaker
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Problem-solving
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Attention to detail
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Adaptability
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Self-motivation
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Effective communication
My Programming Journey
Since I was a kid, I always had a curiosity about computers. People often told me I should study something related to technology, and I liked the idea—it felt so hands-on and practical. When I got older, though, I didn’t start learning programming right away. At 23, I finally decided to dive in. I knew it was late, but I also knew I didn’t have a choice. I hadn’t started sooner because no one around me really talked about programming or guided me toward it.
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One day, I decided to study Python after hearing that data science was an exciting field. I spent about three months learning Python and thought I was close to mastering data science. But then I realized I was barely scratching the surface—I didn’t understand how complex working with data could be. When I looked up the data science roadmap, I felt overwhelmed. I saw how long the journey could be, and for a few days, I lost motivation, wondering if I’d ever get there.
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But I decided to stick with it, starting with Python libraries like Pandas, Seaborn, and NumPy to build up essential data analysis skills. I took things one step at a time, slowly gaining confidence as I learned more. Today, I’m grateful that I kept going. I’m much further than I was when I started, and I keep discovering new things all the time.