Proficient in Python programming language for data analysis and visualization.
Expertise in SQL for database management and querying.
Skilled in creating interactive visualizations and business intelligence dashboards using Power BI.
Proficient in creating data visualizations and dashboards using Tableau.
Experience in implementing machine learning algorithms for predictive modeling and data analysis.
Proficient in Microsoft Office Suite, including Word, Excel, and PowerPoint.
Advanced skills in Excel, including data analysis, pivot tables, and macros.
Experience in using Jira for project management and issue tracking.
Proficient in version control using Git for collaborative software development.
Experience with Atlassian tools such as Jira and Confluence for project management and collaboration.
Experience with Extract, Transform, Load (ETL) processes for data integration and data warehousing.
Experience in using Google Colab for running Python code and machine learning experiments in the cloud.
Experience with Amazon Web Services (AWS) cloud platform for deploying and managing applications.
Proficient in using Microsoft Windows operating system.
Experience with Linux operating system.
Embark on a journey into the world of fitness with our Fitlife Hub Database System. Designed to revolutionize fitness monitoring, this project employs cutting-edge technology including MySQL, Python, and Neo4j. Dive deep into the realms of ER modeling, UML, and Hierarchical Data Modeling as we sculpt a data-driven fitness paradise. Witness the magic unfold as stored procedures, joins, and triggers work in harmony, enhancing efficiency by a staggering 15%. Are you ready to sculpt your data-driven fitness masterpiece?
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Unlock the secrets hidden within your data with our Customer Segmentation project. Marvel as we ensure near-perfect data integrity through an exhilarating journey of Data Cleaning, Transformation, and Outlier handling. With the power of advanced statistical analysis and machine learning techniques like linear regression, witness customer behavior come to life. Delve into the world of customer cohorts through RFM analysis and K-means clustering, as we unveil the hidden gems buried within your data. Get ready to revolutionize your business strategy with data-driven insights!
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Embark on a journey into the depths of neural patterns with our EEG Classification Model. Witness the marvels of modern medicine as we develop an epilepsy diagnosis tool using Python's sklearn libraries. Brace yourself as neural networks with TensorFlow and Keras reach unprecedented heights, achieving 85% RNN and 92% CNN accuracy. Explore the realms of medical science as we tackle missing data, reduce noise, and extract features from time series and discrete domains. Are you ready to unveil the mysteries hidden within EEG data?
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Delve into the crucial realm of mental health analysis with our comprehensive project focused on stress and well-being. Through this project, we explore the multifaceted aspects of mental health, examining factors such as stressors, coping mechanisms, and overall well-being. Using advanced data analysis techniques, we uncover insights into the prevalence of mental health issues, their impact on individuals, and strategies for intervention and support. Join us in understanding the complexities of mental health through data-driven exploration and analysis!
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Explore the fascinating world of global data science and analytics salaries through our captivating Tableau dashboard project. Immerse yourself in an interactive exploration across various countries, uncovering the intricacies of data scientist and analyst compensation. Harnessing the power of Tableau's visualization capabilities, we unveil salary trends, regional disparities, and industry insights with stunning clarity. Get ready to embark on a data-driven journey that will revolutionize your understanding of data science compensation worldwide!
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Dive into the realm of environmental sustainability with our project on Predictive Modeling of CO2 Emissions. Harnessing the power of machine learning models such as Linear, Lasso, K-Nearest Neighbors, and Random Forest, we delve deep into predicting CO2 emissions with remarkable precision. Leveraging Python libraries like scikit-learn and pandas, we achieved outstanding results with 92% R-squared values. With hyperparameter optimization techniques such as Randomized Search and Grid Search, we fine-tuned model performance to enhance predictive accuracy to an impressive 97%.
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Hi there! I'm Aishwariya Alagesan, a data enthusiast currently pursuing my Master's in Data Analytics Engineering at Northeastern University, Boston. I'm passionate about uncovering insights from data.
With expertise in Python, SQL, Power BI, and Tableau, I enjoy working with databases like MySQL and Oracle. Whether it's cleaning datasets or creating interactive visualizations, I'm always eager to dive into the data.
When I'm not analyzing data, you'll find me exploring new analytical techniques or enjoying a cup of coffee. With a curious mind and a love for data, I'm ready to tackle any data challenge!
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