Complete ML toolkit: Naive Bayes, Decision Trees, Random Forest, XGBoost, K-Means — Google Advanced Data Analytics
Automated EDA pipeline with reusable visualization wrappers — Google Advanced Data Analytics
Linear/logistic regression, hypothesis testing, and model evaluation — Google Advanced Data Analytics
Reusable Python utilities for data loading, EDA, and cleaning — Google Advanced Data Analytics
End-to-end ML capstone with 3 scenarios (Automatidata, TikTok, Waze) — Google Advanced Data Analytics
About The Google Advanced Data Analytics Certificate contains information on how to use machine learning, predictive modeling, and experimental design to collect and analyze large amounts of data, and prepare for jobs like Senior Data Analyst and Junior Data Scientist.
My personal project for the Google Advanced Data Analytics capstone project.
Coursework and applied projects from the Google Advanced Data Analytics Professional Certificate, covering Python, EDA, statistics, hypothesis testing, confidence intervals, regression, data visualization, and machine learning—including K-means clustering and real-world business case studies.
End-to-end ML pipeline predicting Waze user churn: EDA, hypothesis testing, logistic regression, and tuned Random Forest & XGBoost models with SHAP feature importance. Google Advanced Data Analytics project.
Case studies of different companies whose multiple data analytics tasks have been studied using Statistical models and Machine Learning in Python
Google Advanced Data Analytics capstone predicting Salifort Motors employee turnover: logistic regression, decision tree, and Random Forest (with SHAP), framed with the PACE methodology and data-driven HR retention recommendations.
Projects I have completed as part of the Google Advanced Data Analytics Certificate.
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