Notes & Curriculum
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6 CoursesIntroduction to Data Science with R
Foundational course covering R programming, data wrangling with dplyr and tidyr, and data visualisation using ggplot2.
Python for Data Analytics
Comprehensive Python course focusing on NumPy, Pandas, Matplotlib, and Seaborn for real-world data analysis.
Biostatistics and Survival Analysis
Advanced statistical methods for health data including Kaplan-Meier, Cox regression, and competing risks.
Machine Learning Fundamentals
From linear regression to neural networks — theory and implementation using scikit-learn and TensorFlow.
Spatial Statistics & GIS Analytics
Spatial data analysis, Poisson regression for point processes, and mapping with ggplot2 and Leaflet.
Database Design & MySQL Practice
Relational database fundamentals, advanced SQL queries, stored procedures, and data modelling.