I am an aspiring Data Engineer with a background in Philosophy, and a keen interest in the intersections of Psychology, Sociology, and Artificial Intelligence. My journey into Data Science and AI has been fueled by a passion for understanding data's role in shaping decisions and insights. I am particularly interested in building efficient data systems and utilizing AI for social good.
- Programming Languages: Python, SQL
- Data Engineering Tools: Apache Spark, Apache Kafka (basic knowledge)
- Databases: PostgreSQL, MySQL
- Cloud Platforms: AWS (S3, RDS), Google Cloud Platform (BigQuery), Azure
- Machine Learning Libraries: TensorFlow, Scikit-Learn
- Big Data Tools: Apache Hadoop, Hive (basic usage)
- Data Analysis Tools: Pandas, NumPy, Matplotlib, Seaborn, and basic Tableau
- Version Control: Git and GitHub
- Data Engineering: Learning how to build and manage data pipelines, and work with large datasets using Apache Spark and Kafka.
- Machine Learning: Exploring foundational machine learning algorithms using Scikit-Learn and TensorFlow.
- Data Analysis: Improving my skills in data cleaning, data manipulation, and visualization using Pandas, NumPy, Matplotlib, and Seaborn.
- Cloud Platforms: Gaining familiarity with data storage and processing services in AWS, Azure and Google Cloud.
- [Data Pipeline Project]: Developing a data pipeline that ingests, transforms, and loads data from multiple sources using Python and PostgreSQL.
- [Basic Machine Learning Models]: Experimenting with simple machine learning models (e.g., linear regression, decision trees) to understand their practical applications.
- [Data Analysis Project]: Working on exploratory data analysis (EDA) and visualizing insights from publicly available datasets using Python and Tableau.
- Bachelor’s Degree in Philosophy with coursework in Psychology and Sociology.
- My academic background informs my data-driven work, providing me with a human-centered and ethical perspective on how data and AI are utilized in different sectors, particularly in social and behavioral contexts.
- Continue building my expertise in data engineering, with a focus on scaling data pipelines and optimizing data workflows.
- Explore advanced topics in AI and machine learning, particularly in the areas of natural language processing (NLP) and deep learning.
- Contribute to open-source projects related to AI ethics, data analysis, and data engineering.
I am open to collaborating on projects that involve data engineering, data analysis, and AI applications, especially in the context of social sciences. If you’re working on something in these areas, feel free to get in touch!
- Email: [[email protected]]
- LinkedIn: [https://www.linkedin.com/in/mustafa-gul00/]
Feel free to check out my repositories where I showcase projects in data analysis, data engineering, and machine learning. Looking forward to connecting with like-minded professionals in these fields!