Programming Languages: Python, R, Java
Expertise in Python and R for data analysis, modeling, and statistical computing.
Hello! I'm
Samreena Siddiqui
UC Berkeley
Undergraduate Student
Hello! I'm
UC Berkeley
Undergraduate Student
Get To Know More
UC Berkeley
Junior, CO '26
Majors: Data Science, BA & Cognitive Science, BA
Machine Learning, Big Data Analytics, AI, Deep Learning, Health Informatics, Behavioral Data Analytics
Foundations of Data Science, Linear Algebra and Differential Equations, The Structure and Interpretations of Computer Science, Data Structures, Principles & Techniques of Data Science, Probability for Data Science
I am an undergraduate student pursuing a double major in Data Science and Cognitive Science at Berkeley, driven by a deep passion for the analytical world. My goal is to leverage data to enhance our understanding of human behavior, bridging the gap between numbers and the nuances of human experience. This ambition was put into practice during my recent internship at Jacob's Ladder, a psycho-therapeutics company. There, I applied my data science skills to analyze and refine therapy programs, ultimately improving their efficiency and effectiveness. This hands-on experience solidified my commitment to using data as a transformative tool in understanding and improving human well-being. I am now actively seeking opportunities to join a data science team that shares my vision and passion. I am eager to contribute my skills and knowledge to projects that have a meaningful impact, and I am fully prepared to bring my best to any role. Please feel free to connect with me through the contact section below if you share similar goals or have opportunities that align with my aspirations.
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Expertise in Python and R for data analysis, modeling, and statistical computing.
Proficiency in Matplotlib, Seaborn, and Plotly for creating clear and informative data visualizations.
Strong foundation in linear algebra, probability, statistics, and calculus for understanding and applying data science techniques.
Experience with regression, classification, clustering, and dimensionality reduction techniques (e.g., PCA) for building predictive models.
Skilled in SQL for database querying, and libraries such as Pandas, NumPy, SciPy, and Scikit-Learn for data manipulation and analysis.
Basic understanding of HTML and CSS for integrating data science projects into web applications or dashboards.
Proficiency in R and Python for analyzing biological data and building computational models in cognitive science.
Expertise in coding and analyzing language data, crucial for research in psycholinguistics and computational linguistics.
Hands-on experience with PCR, staining, and gel electrophoresis for studying molecular aspects of brain function.
Strong ability to write research papers and present findings clearly to both academic and general audiences.
Familiarity with designing and implementing neural networks for modeling cognitive processes and understanding brain function.
Broad understanding of brain anatomy, neuroimaging techniques, and cognitive processes to integrate insights from various disciplines.
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